NLP Jobs in Mumbai

Deputy Vice President Data Science Location: Mumbai Function: Technology Digital and Data Sciences Employment Type: Full Time Experience: 9-10 years Key Responsibilities AI & Machine Learning: Design, develop, and deploy machine learning models for predictive analytics, natural language processing (NLP), computer vision, and recommendation systems. Lead end-to-end AI project lifecycles, including model validation, production deployment, and ongoing optimization using frameworks such as TensorFlow, PyTorch, and scikit-learn. Stay abreast of the latest advancements in Generative AI and foundational models, evaluating their applicability and integration within business solutions. Collaborate with cross-functional teams to identify AI use cases and deliver tangible business impact. Data Science & Analytics: Drive the entire analytics lifecycle, from data exploration and modeling to delivering actionable insights and developing data-driven products. Partner with data engineers and analysts to develop scalable, impactful solutions that support business objectives. Leadership & Strategy: Mentor and develop junior data science professionals, fostering a culture of continuous learning and innovation. Contribute to the organization s AI and cloud strategy by helping define the roadmap and setting long-term vision. Cloud Architecture & Engineering: Architect and design scalable, cloud-native AI and data platforms primarily on Google Cloud Platform (GCP), with knowledge of AWS and Azure as alternatives. Optimize data pipelines and machine learning workflows using cloud services such as Vertex AI, SageMaker, or Azure ML. Ensure the design and implementation of secure, cost-effective, and scalable architectures supported by robust CI/CD pipelines.

Deputy Vice President Data Science Location: Mumbai Function: Technology Digital and Data Sciences Employment Type: Full Time Role Overview We are seeking a seasoned and innovative Deputy Vice President Data Science to lead cutting-edge AI and data science initiatives. The ideal candidate will drive the development and deployment of machine learning models, architect cloud-native AI platforms, and guide strategic transformation through advanced analytics. This role requires strong leadership, deep technical expertise, and the ability to collaborate across business and technology teams to deliver measurable impact. Key Responsibilities AI & Machine Learning: Design, develop, and implement advanced machine learning models for predictive analytics, NLP, computer vision, and recommendation engines. Lead end-to-end AI project lifecycles, including model validation, productionization, and continuous optimization using frameworks like TensorFlow, PyTorch, and scikit-learn. Stay current with the latest developments in Generative AI, foundation models, and LLMs; evaluate and integrate them into solutions where applicable. Identify and prioritize AI use cases in collaboration with cross-functional teams to create business value. Data Science & Analytics: Lead the complete analytics lifecycle from data exploration and model building to insight generation and product deployment. Work closely with data engineers and analysts to develop scalable, high-impact solutions that influence business outcomes. Leadership & Strategy: Mentor and develop junior team members, promoting a culture of learning, experimentation, and excellence. Contribute to enterprise-wide AI and cloud strategies, including vision setting and roadmap development. Cloud Architecture & Engineering: Architect and implement cloud-native AI and data platforms on GCP (preferred), with working knowledge of AWS or Azure. Build and optimize scalable ML workflows and data pipelines using platforms like Vertex AI, SageMaker, or Azure ML. Ensure secure, scalable, and cost-effective infrastructure, supported by CI/CD pipelines and MLOps best practices. Required Skills & Qualifications Technical Proficiency: Strong coding skills in Python and SQL. Expert-level knowledge of ML frameworks: TensorFlow, PyTorch, Hugging Face, scikit-learn. Practical experience with Large Language Models (LLMs), vector databases, and Retrieval-Augmented Generation (RAG) techniques. Cloud & Engineering: Proficient in designing solutions on Google Cloud Platform (GCP); experience with AWS or Azure is a plus. Familiarity with data tools like BigQuery, Kafka, Snowflake. Strong knowledge of MLOps, including CI/CD pipelines, model monitoring, and A/B testing frameworks. Governance & Ethics: Solid understanding of data privacy, governance, and responsible AI principles.

Position: Machine Learning Engineer Location: Vile Parle, Mumbai, Maharashtra, India Job Type: Full-Time About the Role: We are seeking an experienced Machine Learning Engineer to lead our efforts in developing Artificial Intelligence (AI) and Natural Language Processing (NLP) based products. You will be responsible for creating machine learning models, retraining systems, and building self-learning applications. The role requires exceptional skills in statistics, programming, and an in-depth understanding of data science and software engineering. Your primary goal will be to shape and build efficient, self-learning applications that meet business objectives. Key Responsibilities: Model Development: Develop machine learning models that help achieve business objectives and establish metrics to track their progress. Resource Management: Manage resources such as hardware, data, and personnel to meet project deadlines. Algorithm Selection: Analyze and rank ML/NLP algorithms based on their likelihood of success in solving a given problem. Data Analysis: Explore and visualize data to understand its nature and identify potential issues that could affect performance when the model is deployed in real-world settings. Data Acquisition & Preparation: Supervise the data acquisition process and identify additional datasets if necessary. Define the data pre-processing and feature engineering strategies required. Model Training & Tuning: Train models, tune hyperparameters, and analyze model errors, implementing strategies to overcome them. Model Deployment: Deploy models to production and ensure they meet operational requirements. Skills and Qualifications: Experience: Minimum of 3 years of experience as an ML/NLP Engineer or in a similar role. Frameworks & Libraries: Proficiency in machine learning frameworks like Keras or PyTorch and libraries such as scikit-learn, pandas. Data Handling: Expertise in visualizing and manipulating large datasets. Text Representation: Deep understanding of text representation techniques like n-grams, bag of words, sentiment analysis, etc. OpenCV: Proficiency with OpenCV for image processing. Hardware Selection: Ability to select and manage hardware to run ML models efficiently, ensuring the required latency is met. Degree: A degree in Computer Science, Mathematics, Computational Linguistics, or a related field. Qualification : Degree in Computer Science, Mathematics, Computational Linguistics or similar field

AI/ML Developer Location: Mumbai Experience: 5+ years Key Responsibilities: AI/ML Solutions Development: Develop, deploy, and maintain scalable AI/ML solutions tailored to the healthcare industry. Data Preprocessing & Structuring: Collaborate with data engineers and analysts to preprocess, clean, and structure healthcare data for machine learning applications. Model Design & Implementation: Design and implement machine learning models for real-world healthcare challenges like patient readmission prediction, disease progression modeling, and medical image analysis. Production Integration: Integrate AI/ML solutions into production environments, ensuring models are efficient, reliable, and meet client goals. Client Collaboration: Work with healthcare clients to define project requirements and KPIs, ensuring the solution brings measurable value. AI/ML Advancements: Stay up to date with the latest advancements in AI/ML, particularly in healthcare, and integrate new techniques to improve solutions. Regulatory Compliance: Ensure all AI/ML applications meet healthcare regulations (e.g., HIPAA, GDPR) and maintain high standards for patient data privacy and security. Model Monitoring & Optimization: Monitor, fine-tune, and update models post-deployment to maintain optimal performance and adapt to evolving healthcare data. Requirements: Experience: 5+ years in AI/ML, deep learning, and machine learning applications, preferably in the healthcare industry. Technical Skills: Proficiency in Python and/or R, with experience in ML libraries like TensorFlow, PyTorch, Scikit-Learn, etc. Healthcare Data Expertise: Strong understanding of healthcare data types and sources (e.g., EHR/EMR data, claims data, imaging data, genomics). Cloud Platforms: Familiarity with cloud platforms (AWS, Azure, Google Cloud) and deploying ML models in these environments. Healthcare ML Use Cases: Experience in healthcare-specific ML use cases such as patient outcome predictions, medical image classification, and NLP for clinical notes. Regulatory Knowledge: Strong understanding of healthcare privacy and regulatory standards (e.g., HIPAA, GDPR). Communication Skills: Excellent problem-solving, analytical, and communication skills, with the ability to convey complex technical ideas to non-technical stakeholders. Shift Flexibility: Ready to work in shifts to accommodate the global nature of healthcare projects. If you're passionate about developing impactful AI/ML solutions in the healthcare industry and have the required expertise, apply now for the AI/ML Developer position in Mumbai!

Job Title: Software Engineer (AI/ML) Location: Mumbai Job Type: Permanent Education: Any Graduate / Post Graduate Experience: 2 to 3 years Openings: 3 What You Will Do: Design, develop, and deploy machine learning models and AI-driven solutions. Pre-process and analyze large datasets to derive actionable insights. Implement and optimize deep learning models, including Natural Language Processing (NLP) and computer vision. Develop and fine-tune algorithms for classification, prediction, and recommendation systems. Leverage cloud platforms (AWS, Azure, GCP) for model training and deployment. Optimize ML models for performance, scalability, and real-time inference. Collaborate with data engineers to build efficient data pipelines. Stay updated with the latest AI/ML advancements and integrate best practices into development. Work closely with cross-functional teams to understand business requirements and deliver AI solutions. Qualifications: Experience: 2-3 years in AI/ML development. Technical Skills: Strong programming skills in Python and experience with libraries like TensorFlow, PyTorch, and Scikit-Learn. Hands-on experience in deep learning, NLP, and computer vision. Expertise in handling large datasets and data pre-processing techniques. Experience in deploying ML models using cloud platforms (AWS SageMaker, Azure ML, GCP AI). Solid knowledge of machine learning algorithms, model evaluation, and hyperparameter tuning. Familiarity with database technologies (SQL, NoSQL) and big data frameworks (Spark, Hadoop). Experience in data pre-processing for structured and unstructured data (text, audio, video). Knowledge of document processing, Vision AI, Audio AI, and building AI-driven systems using Langchain and Rasa. Experience building AI chatbots and voicebots. Familiarity with DevOps and CI/CD for cloud platforms (AWS, Azure, GCP). Experience working in Agile SDLC with an iterative development mindset. Strong logical, analytical, and creative thinking, with a passion for problem-solving. Qualification : Any Graduate / Post Graduate

Job Title: Senior Software Engineer (AI/ML) Location: Mumbai Job Type: Permanent Education: Any Graduate / Post Graduate Experience: 4 to 6 years Openings: 2 What You Will Do: Design, develop, and deploy machine learning models and AI-driven solutions. Pre-process and analyze large datasets to extract meaningful insights. Implement and optimize deep learning and NLP models for various applications. Develop and fine-tune algorithms for classification, prediction, and recommendation systems. Leverage cloud platforms (AWS, Azure, GCP) for model training, deployment, and scalability. Optimize ML models for high performance, scalability, and real-time inference. Collaborate with data engineers to build efficient and reliable data pipelines. Stay updated with the latest advancements in AI/ML technologies and best practices. Work closely with cross-functional teams to understand business requirements and deliver AI solutions that address key business challenges. What Qualifications You Will Need: Experience: 4-6 years in AI/ML development, with a focus on building real-world AI systems. Technical Skills: Strong programming skills in Python, with hands-on experience in libraries like TensorFlow, PyTorch, and Scikit-Learn. Proficiency in deep learning, NLP, and computer vision. Expertise in working with large datasets and employing data pre-processing techniques. Experience in deploying machine learning models using cloud platforms (AWS SageMaker, Azure ML, GCP AI). Solid understanding of machine learning algorithms, model evaluation, and hyperparameter tuning. Familiarity with database technologies (SQL, NoSQL) and big data frameworks (Spark, Hadoop). Experience in data pre-processing for both structured and unstructured data (e.g., text, audio, video). Knowledge of document processing, Vision AI, and Audio AI technologies. Experience building AI agentic systems using Langchain and Rasa. Hands-on experience with developing AI chatbots and voicebots. Familiarity with DevOps practices and CI/CD pipelines (AWS, Azure, GCP). Experience working in Agile SDLC with an iterative development mindset. Strong logical, analytical, and creative problem-solving abilities. Qualification : Any Graduate / Post Graduate

Job Title: Tech Lead (AI/ML) Location: Mumbai Job Type: Permanent Education: Any Graduate / Post Graduate Experience: 7 to 10 years Openings: 2 What You Will Do: Lead the design and development of scalable, high-performance AI/ML solutions. Define and implement AI/ML architecture and best practices across the team. Guide and mentor the AI/ML team in model development, optimization, and deployment. Work with large datasets to preprocess, analyze, and extract meaningful insights. Develop and optimize deep learning, NLP, and computer vision models. Architect end-to-end AI/ML pipelines, including data collection, model training, and deployment. Implement MLOps practices for continuous integration, deployment, and monitoring of ML models. Leverage cloud platforms (AWS, Azure, GCP) to deliver scalable AI/ML solutions. Collaborate with cross-functional teams to understand business challenges and deliver impactful AI-driven solutions. Stay abreast of the latest advancements in AI/ML and drive innovation within the team. What Qualifications You Will Need: Experience: 7-10 years in AI/ML development, with hands-on experience in designing and architecting AI/ML solutions. Technical Skills: Strong programming skills in Python. Expertise in deep learning, NLP, computer vision, and recommendation systems. Strong knowledge of data engineering, feature engineering, and automation of data pipelines. Experience in deploying AI/ML models on cloud platforms (AWS, Azure, GCP). Familiarity with big data technologies (Spark, Hadoop) and database management (SQL, NoSQL). Proven ability to build and manage end-to-end production-grade AI services. Strong understanding of AI systems architecture. Ownership of solution quality, including functional, technical, performance, and compliance aspects. Hands-on experience with MLOps practices for continuous integration and deployment of ML models. Focus on leveraging AI to improve business outcomes. Deep interest in staying updated with the latest trends in the AI/ML field. Leadership mindset with the ability to guide and mentor developers. Experience with data pre-processing for structured and unstructured data (text, audio, video). Familiarity with document processing, Vision AI, and Audio AI. Expertise in building AI agentic systems using Langchain and Rasa. Experience with AI chatbots and voicebots. Familiarity with DevOps and CI/CD pipelines on cloud platforms (AWS, Azure, GCP). Experience working in Agile SDLC with an iterative development mindset. Strong logical, analytical, and creative problem-solving skills. Qualification : Any Graduate / Post Graduate

Position: Natural Language Processing (NLP) Engineer - Fundamental Fixed Income Team About the Role: BlackRock's active fixed income portfolio strategies span across a wide range of investment styles and segments, with a focus on alpha generation and risk management. The team uses a combination of top-down insights from lead portfolio managers and bottom-up expertise from sector specialists to deliver attractive returns in various market conditions. Join the Fundamental Fixed Income team and make a significant impact by using advanced data science techniques to solve complex problems in finance. Your Responsibilities: Work with advanced natural language processing (NLP) tools like SpaCy, NLTK, or Hugging Face, with an understanding of implementing Vector Databases. Follow best programming practices such as unit tests, code organization, and basics of CI/CD to create well-maintainable and tested codebases. Develop prototypes for individual components of software or data science solutions, leveraging basic data structures and algorithms. Collaborate with peers within PMG and iHub India (MASS Labs, RQA Labs, AI Labs) to continue research on use cases developed within firm-wide initiatives. Education and Qualifications/Skills: 7-12 years of experience in a relevant field. Motivated team player with the ability to work independently and flexibly. Proficiency in Python, including experience with machine learning libraries such as TensorFlow, PyTorch, or Keras. Solid understanding of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory. Knowledge of at least one domain such as generative AI, statistical learning, optimization, NLP, deep learning, or time series analysis. A passion for solving real-world finance problems using data science and machine learning approaches. Strong analytical thinking skills and ability to creatively solve business problems. Experience with data exploration, analysis, and creating visualizations, and implementing algorithmic solutions in ML. Self-driven, results-oriented, and able to collaborate effectively across time zones and geographies. Our Benefits: To help you stay energized, engaged, and inspired, we offer a wide range of benefits including: A strong retirement plan. Tuition reimbursement. Comprehensive healthcare options. Support for working parents and Flexible Time Off (FTO) to recharge. Our Hybrid Work Model: BlackRock s hybrid work model supports collaboration while offering flexibility. Employees are required to work at least 4 days in the office per week, with the option to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. About BlackRock: At BlackRock, we are united by one mission: helping more people experience financial well-being. Our clients use their investments to save for retirement, pay for education, buy homes, and start businesses. These investments strengthen the global economy, supporting businesses large and small, financing infrastructure projects, and fueling innovations. Our mission would not be possible without our greatest investment our people. We re committed to fostering an environment where employees feel welcomed, valued, and supported with benefits, networks, and opportunities for growth.

Role Summary We are currently seeking a talented Data Scientist specializing in Campaign Effectiveness Analysis to join our dynamic team. The ideal candidate will be instrumental in advanced modeling, twinning, imputation, and analytics, focusing on supporting Campaign Effectiveness accounts and projects. Key Responsibilities Conduct causal inference, including hierarchical modeling, difference-in-differences, and using controls, with expertise in longitudinal design. Apply Machine Learning skills for imputation and quick drivers analyses. Familiarity with Campaign Effectiveness data and database, including an understanding of the unique methodologies required for this design. Execute modeling tasks in R for complex analyses. Utilize SPSS for ad hoc exploratory data analysis. Proficient in SQL for data retrieval, manipulation, and database creation across multiple studies. Perform static annual norms calculations efficiently, with knowledge of post-curve completion code. Contribute to institutional knowledge regarding normative standards, cleanup processes, and consequences. Execute data pulls for curves using SQL, ensuring alignment with normative standards. Manage years of curves in an R-based application involving thousands of curves. Join curves to an adjustment file through modeling. Conduct all procedures and cleaning in R, recognizing the time-intensive nature of replicating processes. Qualifications Education: Bachelor s or advanced degree in Data Science, Statistics, Computer Science, or related field. Competencies Desired Proven experience as a Data Scientist, preferably in Campaign Effectiveness or Market Research domain. Expertise in causal inference, machine learning, and SQL. Proficiency in advanced R program for modeling and analytics. Experience with SPSS for data exploration. Strong understanding of data governance and database management. Qualification : Bachelors or advanced degree in Data Science, Statistics, Computer Science, or related field.

Data Scientist Location: Mumbai Experience: 2 7 years Employment Type: Full-Time About the Role We are looking for a highly skilled and motivated Data Scientist to join our team in Mumbai. The ideal candidate will have a strong background in data science, machine learning, and big data technologies, with the ability to draw actionable insights from complex data sets. If you're passionate about solving real-world problems using data and AI, and thrive in a fast-paced, collaborative environment we want to hear from you. Key Responsibilities Design and implement processes to collect and aggregate data from multiple sources. Clean, normalize, and prepare large datasets for analysis. Apply statistical methods and machine learning techniques to uncover insights and drive business decisions. Build scalable data pipelines and frameworks to manage large volumes of data. Work cross-functionally to develop innovative products, reports, and features aligned with business needs. Translate analytical findings into clear, actionable recommendations. Desired Candidate Profile 2 7 years of relevant experience in data science or related fields. Proficiency in Python, R, and SQL. Strong grasp of machine learning, AI, and natural language processing (NLP). Experience with big data technologies and handling large datasets. Excellent knowledge of algorithms, mathematics, and statistics. Ability to thrive in a dynamic, challenging environment. Strong problem-solving and communication skills. High attention to detail and analytical rigor. Opportunity to work on cutting-edge data-driven solutions. Collaborative and innovative work culture. Chance to shape impactful products and features in real-world applications. Career growth and learning in advanced data technologies and AI.

Quantitative Researcher Location: Mumbai Company: Qube Research & Technologies (QRT) Job Type: Full-Time Your Future Role at QRT As a Quantitative Researcher, your primary objective will be to develop high-quality predictive signals by analyzing large and diverse datasets to identify statistical patterns and trading opportunities. You will collaborate closely with fellow researchers to share methodologies, data sets, and results, contributing to the continuous improvement of QRT s global execution platform. Monitoring and refining model performance over time will be key to maintaining the effectiveness of your strategies. Key Responsibilities Develop and validate predictive signals using advanced quantitative techniques. Analyze large datasets across multiple time frames to uncover meaningful patterns and opportunities. Collaborate with other researchers to share insights, methodologies, and datasets. Implement trading signals and integrate relevant datasets within QRT s execution platform. Continuously monitor signal behavior and model performance, making improvements as needed. Your Present Skillset Advanced degree in a quantitative discipline such as Data Science, Statistics, Mathematics, Physics, Engineering, or a related field. Proficiency in at least one programming language commonly used in quantitative research (e.g., Python, R, Matlab, C++, C#). Strong foundation in statistics, machine learning, NLP, or AI techniques is an advantage. Experience working with large datasets and conducting analysis across multiple time frames is a plus. Ability to multitask effectively in a fast-paced environment while maintaining attention to detail. Intellectual curiosity and a passion for solving complex problems by exploring new data sources and innovative methods. Capacity to work autonomously while contributing positively within a collaborative team environment.

Quantitative Researcher Macro Location: Mumbai Company: Qube Research & Technologies (QRT) Job Type: Full-Time About QRT QRT is a global quantitative and systematic investment manager operating across all liquid asset classes worldwide. We leverage technology, data, and research combined with trading expertise to solve complex challenges and generate high-quality returns for our investors. Our culture of innovation and collaboration drives our ambition to remain at the forefront of quantitative investing. Your Future Role within QRT As a Quantitative Researcher specializing in Macro strategies, you will lead the end-to-end research process from signal generation through implementation. Your primary goal will be to develop high-quality predictive signals by analyzing large and diverse macroeconomic datasets, identifying statistical patterns and investment opportunities. You will collaborate globally with researchers, data scientists, technologists, and traders to share methodologies and improve strategy performance over time. Key Responsibilities Lead full-cycle strategy research: signal generation, testing, implementation, and ongoing monitoring. Analyze large, diverse datasets to identify meaningful macroeconomic statistical patterns and opportunities. Collaborate and communicate research results, data sets, and processes with global teams. Integrate signals and datasets into QRT s global execution platform. Continuously track and optimize model performance within your strategies. Your Present Skillset Minimum 3 years of relevant experience with a proven track record in systematic strategy development. Advanced degree in a quantitative field such as Data Science, Statistics, Mathematics, Physics, Engineering, or related disciplines. Strong knowledge of statistics, machine learning, NLP, or AI techniques is advantageous. Proficiency in at least one major programming language (Python, R, Matlab, C++, C#). Experience analyzing large datasets across multiple time frames is a plus. Ability to multitask and maintain high attention to detail in a fast-paced environment. Intellectual curiosity and problem-solving mindset to explore new data sources and innovative research processes. Ability to work independently while contributing effectively within a collaborative global team. Excellent communication skills to engage with technologists, data scientists, and traders worldwide. Equal opportunity employer fostering a diverse and inclusive workplace. Empowering employees to work openly and respectfully for collective success. Comprehensive programs supporting healthy work-life balance alongside professional growth.

Company Overview Mondel z International is a leading global snacking company with iconic brands like Oreo, Cadbury, and Toblerone. The company s mission is to lead the future of snacking, creating delicious moments of joy for people around the world. As part of Mondel z's dynamic Digital Solutions team, this role will offer an exciting opportunity to drive innovation through AI, data, and analytics. Role Overview As a Data Scientist within the Mondelez Digital Solutions team, you will play a critical role in developing cutting-edge AI and GenAI solutions that will empower the US Sales & Planning teams. This role focuses on leveraging Analytical AI algorithms and Large Language Models (LLMs) to create actionable insights and transform commercial reporting processes. You'll work closely with multiple teams to implement these solutions and continuously improve the reporting and decision-making capabilities of the organization. How You Will Contribute 1. AI and GenAI Model Development Design, develop, and deploy Analytical AI models (e.g., linear regression, decision trees, boosted trees models) to gather insights related to customers, brands, categories, and products. Implement anomaly detection algorithms (e.g., isolation forest) to identify anomalies in commercial data and alert teams about significant changes. Utilize Large Language Models (LLMs) to summarize the current business state and explain trends in the data, supporting the commercial reporting team. 2. Data Preparation and Utilization Oversee the extraction, preparation, and utilization of large datasets for model training and validation, ensuring the data is clean, accurate, and relevant for AI model development. Continuously update and refine the AI/GenAI solution with new data sources and features to enhance business insights. 3. Collaboration and Implementation Work closely with cross-functional teams to ensure smooth deployment of AI and GenAI capabilities into the company s commercial reporting dashboards. Collaborate with stakeholders to ensure the tools meet business requirements and deliver high-quality insights. 4. Reporting and Documentation Regularly report on the achievements and challenges of the AI tools to senior management and relevant stakeholders. Maintain detailed documentation of AI models, GenAI solutions, logic, and performance metrics, ensuring the business can leverage insights effectively. 5. Continuous Improvement and Innovation Stay up to date with the latest trends in AI and GenAI and integrate new advancements into the reporting system to improve its efficiency and effectiveness. What You Will Bring 1. Required Skills & Experience Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, or related fields. Strong analytical and critical thinking skills with the ability to translate complex data into actionable business strategies. Proficiency in handling large datasets using Python and SQL. Strong knowledge of data visualization tools such as Tableau and Power BI. Experience with cloud platforms (e.g., Google Cloud, Azure, Databricks) for deploying AI solutions. Experience with data preprocessing, cleaning, and ETL processes. Familiarity with Natural Language Processing (NLP) techniques. Knowledge of recent advancements and trends in GenAI and a passion for continuous learning in this field. 2. Additional Skills (Good to Have) Working knowledge of syndicated data (e.g., Nielsen/IRI or other retail sales data sources). Proficiency in using data containerization and orchestration tools for maintaining complex data workflows. Experience with programming languages like PySpark and R. Experience in leveraging Large Language Models (LLMs) to build GenAI solutions or proofs-of-concept. Experience with frameworks like Langchain for building language applications. Relocation and Support Within-country relocation support is available. For candidates voluntarily moving internationally, minimal support is offered through the Volunteer International Transfer Policy. Qualification : Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, or a related field.

Crypto Quantitative Researcher Location: Mumbai Company: Qube Research & Technologies (QRT) Job Type: Full-Time About QRT Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating across all liquid asset classes. We are a data- and technology-driven firm that applies scientific methodologies to investing. Our collaborative, research-oriented culture enables us to solve complex challenges, continuously innovate, and deliver exceptional results for our investors. Role Overview We are seeking a Crypto Quantitative Researcher to join our elite global research team. In this role, your primary objective is to develop high-quality, predictive trading signals using large-scale crypto and financial datasets. You will conduct in-depth quantitative research, design and test strategies, and implement them into our production environment with support from cutting-edge infrastructure. Key Responsibilities Develop, test, and implement systematic crypto trading strategies based on predictive models and statistical patterns. Leverage structured and unstructured datasets to identify actionable insights in the digital assets space. Collaborate with fellow researchers, data scientists, and technologists to discuss methodologies, share research, and optimize signals. Integrate signals into QRT s global execution platform and monitor performance over time. Stay informed about emerging trends in cryptocurrency, decentralized finance (DeFi), and blockchain ecosystems. Required Qualifications & Experience Experience: Proven track record in developing and implementing systematic crypto strategies. Minimum 2 years of experience in quantitative research or trading within the financial industry. Education: Advanced degree (Master s/Ph.D.) in a quantitative discipline such as Mathematics, Statistics, Data Science, Physics, or Engineering. Skills & Knowledge: Strong statistical analysis and machine learning capabilities; NLP/AI experience is a plus. Deep understanding of crypto markets, DeFi protocols, and blockchain data (preferred). Proficient coding skills in Python (required); knowledge of C++ is a plus. Experience with production-level systems and latency-sensitive environments is advantageous. Ability to work independently while thriving in a collaborative, high-performance culture. Strong communication skills to work effectively with global, cross-functional teams. Work in a high-impact role within a research-led, collaborative environment. Access to sophisticated infrastructure and proprietary data. Competitive compensation aligned with performance. Programs to support wellness and a healthy work-life balance. A diverse, inclusive, and intellectually stimulating workplace. Qualification : Advanced degree (Masters/Ph.D.) in a quantitative discipline such as Mathematics, Statistics, Data Science, Physics, or Engineering.

Job Title: Data Collection Transformation Senior Associate Location: Mumbai Experience: Relevant experience in data acquisition, ESG data management, process automation, and data quality. Company: MSCI About MSCI: MSCI is a global leader in decision-support tools and services for the investment community. With over 50 years of expertise in research, data, and technology, we help clients understand key drivers of risk and return, enabling them to build more effective portfolios with enhanced transparency. At MSCI, we foster a culture of innovation, high performance, and inclusion, empowering our people to grow their careers through continuous learning and a wide range of internal mobility opportunities. Your Team: The ESG Data Collection team plays a critical role in acquiring, validating, and maintaining high-quality ESG data that powers MSCI s ESG products. As part of this team, you will work at the forefront of MSCI s ESG transformation agenda, driving projects that enhance data quality, scalability, and automation to meet the evolving ESG landscape and its growing importance in global financial markets. Your Key Responsibilities: Collaborate with internal ESG Research and Technology teams to design and operationalize data collection processes aligned with evolving ESG and Climate frameworks. Work on electronification of ESG policies and principles by converting them into structured, operational data definitions. Develop data collection templates and translate them into implementable data models. Conduct hands-on research and analysis of company disclosures to support scalable data collection solutions. Analyze collected and third-party datasets to detect patterns and trends, enabling development of automated anomaly detection frameworks. Design and implement contextual/thematic QA checks to strengthen data quality controls, leveraging historical data correction patterns. Collaborate with technology teams to build NLP-driven data extraction models (leveraging both traditional methods and LLMs) to automate identification and extraction of relevant ESG facts from disclosures. Help establish and optimize new data collection processes while ensuring seamless integration with existing workflows. Deliver high-quality data aligned with MSCI methodology, service-level agreements, and regulatory requirements. Contribute to creating methodology and SOP documentation, embedding data and content expertise into internal processes. Drive process automation by developing tools and systems for automated data quality diagnostics, reducing manual intervention. Build dashboards and reports to visualize data quality metrics, identify outliers, and provide data-driven recommendations to stakeholders. Partner with internal stakeholders, including downstream teams, Research, and Product teams, to understand data requirements and ensure seamless delivery. What We re Looking For: Strong analytical mindset with a keen attention to detail. Hands-on experience with Python/SQL for data analysis and process automation; exposure to Machine Learning/RPA is a plus. Experience working with visualization tools such as Power BI. Advanced Excel skills, with the ability to manipulate and analyze complex datasets. Self-starter with strong problem-solving abilities, capable of working in unstructured environments. Strong collaboration and communication skills, with comfort working across hierarchies, functions, and geographies. Previous experience in Financial Services, Technology, or Business Analysis, ideally with exposure to ESG data. Basic understanding of financial markets and asset classes; ESG knowledge would be a significant advantage. Preferred Qualifications: Bachelor s or Master s degree in Finance, Economics, Environmental Science, Data Science, Business, or a related field. Certifications in ESG, Sustainable Finance, or Data Analytics are a plus. What We Offer: Transparent compensation and comprehensive benefits tailored to your location. Flexible work options and access to cutting-edge technology. A culture of learning and development, with access to LinkedIn Learning Pro and Learning@MSCI. Clear career progression paths with opportunities for internal mobility and leadership development. A global network of talented colleagues, supported by inclusive Employee Resource Groups like Women in Tech, Climate Action Network, and more. Qualification : Bachelors or Masters degree in Finance, Economics, Environmental Science, Data Science, Business, or a related field.