Plotly Jobs in Bengaluru

Job Description We are seeking a highly skilled Data Acquisition Platform Engineer to join our dynamic team and help build AI/ML-driven solutions that process and classify unstructured data from diverse sources. This role involves designing and developing Python-based systems for data acquisition, processing, and deployment on GCP cloud. You will work with cutting-edge technologies to create solutions that integrate AI/ML models to parse and make data available for downstream consumption. Your Team Responsibilities Data Acquisition: Work on building a platform that acquires unstructured data from multiple sources such as financial documents, websites, and news. Data Processing: Utilize AI/ML models to map, classify, and process unstructured data for downstream system consumption. Cloud Deployment: Deploy the application on Google Cloud Platform (GCP) through DevOps processes, ensuring seamless and scalable operations. Model Management: Create, fine-tune, and deploy Machine Learning models (LLMs) for data classification, parsing, and processing. Application Maintenance: Manage and monitor the platform through various dashboards, ensuring it meets performance and reliability standards. Your Key Responsibilities Design and develop Python-based applications that leverage AI/ML technologies for unstructured data acquisition and processing. Deploy applications using DevOps methodologies on GCP or Azure cloud environments. Build and maintain Machine Learning models for tasks such as text classification, data parsing, and integration. Create interactive dashboards for monitoring and maintaining system performance. Continuously innovate by implementing and integrating the latest advancements in AI/ML, particularly in Natural Language Processing (NLP) and Transformers. Skills and Experience That Will Help You Excel 1. Python & Machine Learning: Strong experience in Python for building scalable data systems and integrating AI/ML models. Expertise in working with Transformers, NLP, and other advanced Machine Learning models for unstructured data processing. 2. Cloud & DevOps: Experience deploying applications on Google Cloud Platform (GCP) or Azure using DevOps tools and processes. Proficiency in building scalable, cloud-native applications that are easy to maintain and monitor. 3. Data Processing & Integration: Knowledge of data parsing, classification, and processing of unstructured data (e.g., text, documents, etc.). Experience in integrating AI/ML models with data pipelines for downstream consumption. 4. Tools and Technologies: Proficiency in DevOps tools for cloud deployment and automation. Familiarity with CI/CD pipelines and tools like Docker, Kubernetes, and Terraform. What We Offer Compensation & Benefits: Transparent compensation schemes and comprehensive employee benefits tailored to your location, ensuring your financial security, health, and overall well-being. Flexible Working: Flexible work arrangements, advanced technology, and collaborative workspaces. Learning & Development: Access to Learning@MSCI, LinkedIn Learning Pro, and customized learning opportunities for continuous professional growth. Career Growth: Multi-directional career paths, offering internal mobility and professional development opportunities. Inclusive Culture: A workplace that embraces diversity and inclusion, supported by various Employee Resource Groups such as Pride & Allies, Women in Tech, and Climate Action Network. Global Network: Work with a talented network of colleagues across the globe and contribute to innovative solutions for the global investment community. Equal Opportunity MSCI is an equal opportunity employer committed to diversifying its workforce. We ensure equal employment opportunities without discrimination or harassment based on race, religion, gender, disability, or any other characteristic protected by law. MSCI is also committed to providing reasonable accommodations for individuals with disabilities.

Position: Data Scientist (AI/ML Expert) Location: Pritech Park SEZ, Block 09, 4th Floor B Wing, Survey No. 51 to 64/4, Outer Ring Road, Bellandur V, Bangalore, Karnataka, India Department: Advanced Analytics Employment Type: Subexian Experience Required: 1 to 3 years Job Overview: We are looking for a talented Data Scientist with expertise in AI/ML to join our Advanced Analytics team. As a key contributor, you ll design, develop, and validate predictive models, recommendation systems, and forecasting solutions, while also collaborating with cross-functional teams to deliver cutting-edge solutions using the latest technologies. Key Responsibilities: Model Development: Design, develop, and validate predictive models, recommendation systems, and forecasting solutions using a mix of statistical, machine learning, and deep learning techniques. You will work both independently and as part of a collaborative team. Data Visualization & Reporting: Communicate actionable insights effectively through compelling dashboards, reports, and visualizations using tools such as Superset, Power BI, and Python libraries (Matplotlib, Seaborn, Plotly). AI & Tech Solutions: Collaborate with teams to design and deliver flexible, scalable solutions using advanced technologies such as AI and large language models (LLMs). API Development: Develop and integrate REST APIs and frameworks such as Flask or FastAPI for seamless deployment of machine learning models. Documentation: Maintain clear, comprehensive documentation for data workflows, model development, and analytical methodologies to ensure knowledge sharing and transparency across teams. Continuous Learning: Stay up-to-date with the latest trends and advancements in data science, algorithms, and technologies, ensuring your skills and knowledge remain cutting-edge. Required Technical Skills: Python Proficiency: Strong experience with Python and libraries like Scikit-learn, TensorFlow/PyTorch, and data visualization libraries (Matplotlib, Seaborn, Plotly). SQL: Solid hands-on experience in SQL for efficient data querying. ML Ops & Pipelines: Understanding of machine learning operations (ML Ops) and ML pipelines for streamlined model deployment. Cloud & Distributed Computing: Exposure to cloud platforms such as AWS, Azure, or GCP and distributed computing tools like Hadoop, Spark, or Pyspark is a plus. Soft Skills: Effective Communication: Strong ability to communicate complex analytical findings in a clear and engaging manner, tailoring insights for both technical and non-technical audiences. Problem-Solving: A proactive problem-solver with the ability to adapt and thrive in a fast-paced, dynamic environment. Continuous Growth: Self-motivated, curious, and always seeking opportunities for professional growth and learning. At Subex, we encourage a collaborative, innovative, and growth-driven work environment. If you're passionate about applying data science techniques to real-world challenges and want to work with cutting-edge AI/ML technologies, we d love to hear from you!

Position: Data Science Specialist Employment Type: Full-time Location: Bangalore, On-site Experience Required: 1 to 6 years (Mindset > Experience) About the Role: We re seeking a mission-driven, hands-on Data Analytics Specialist passionate about impact. This is not a typical analytics role you will drive key business metrics across clinical operations, stakeholder reporting, and automation. Collaborate closely with leadership, radiologists, operations, product teams, and AI engineers to ensure every decision is data-driven, actionable, and scalable. If you thrive on building dashboards, automating processes, streamlining pipelines, and driving growth through insights, this is your playground. Key Responsibilities: Own Business KPIs: Take full ownership of company-wide metrics, ensuring their accuracy, relevance, and actionability through stakeholder alignment. Data Engineering: Build and optimize ETL/ELT pipelines integrating data from Postgres, ClickHouse, and other sources. Dashboards & Reporting: Design and maintain intuitive dashboards (Metabase, Power BI, Tableau, Google Data Studio) that stakeholders actively use. Backend Data Transformation: Write clean, reusable code to convert raw data into actionable insights. API Development: Build and maintain internal APIs to serve analytics data to frontend and production systems. Email Automation: Develop real-time and scheduled email reports delivering dynamic insights to stakeholders. Spreadsheet Expertise: Automate and manipulate complex data in Excel/Google Sheets for detailed analysis and reporting. AI & Automation: Collaborate with AI teams to integrate predictive algorithms and automate analytics workflows. Business Acumen: Develop deep understanding of the teleradiology ecosystem clinical workflows, operations, financials, and tech platforms. Proactive Collaboration: Identify data gaps, flag inconsistencies, recommend improvements, and work closely with leadership. Required Skills: Strong Python skills for data analytics (Pandas, NumPy, FastAPI, Jupyter, etc.) Proficient in SQL (ClickHouse, PostgreSQL) with experience optimizing queries End-to-end dashboard ownership from data modeling to UI presentation Experience building or integrating APIs for analytics Advanced spreadsheet skills and formula-driven reporting Experience working with AI/ML models in applied settings (preferred) Hands-on backend data transformations, version control, and automation Familiarity with full-stack development frameworks (bonus) Bonus / Nice to Have: Exposure to dbt, Airflow, ChromaDB, Streamlit, Plotly Knowledge of data privacy, compliance, and healthcare analytics Experience building analytics platforms for SaaS or health-tech companies Mindset We re Looking For: 10x Hustler: Ready to learn fast and go the extra mile to solve problems. Obsessed with Accuracy: Data must be flawless before release. Extreme Ownership: Proactive in driving results without waiting for instructions. Fast Learner: Able to pick up new tools and concepts quickly. Business First, Code Later: Focused on impact, not just coding. Be part of India s fastest-growing teleradiology platform Direct access to leadership and real-world business impact Build game-changing analytics systems and influence strategy Gain exposure to AI, automation, product, and operations in one role Clear ramp-up roadmap and growth plan Expectations in First 3 Months: Build an end-to-end dashboard from scratch Clean up at least one messy data pipeline Automate a stakeholder email update Validate accuracy across critical business metrics Understand full-stack platform structure and propose an improvement

Role: Senior Analyst Data Engineering Location: Bengaluru, Karnataka, India Experience: 3 6 Years Employment Type: Permanent, Full-Time About the Role We are looking for a results-driven Senior Data Engineer to join our high-performing data team in Bengaluru. The ideal candidate will have 3 6 years of experience in data engineering, AI/ML implementation, and working with large-scale databases like Snowflake and Teradata. If you're passionate about driving data-powered insights, building scalable solutions, and applying advanced machine learning and AI techniques, we want to hear from you. Key Responsibilities Design, develop, and implement machine learning models to solve complex business challenges. Apply AI techniques, including generative AI, NLP, and computer vision, to improve analytics capabilities. Use Tableau, Power BI, and other tools to develop insightful, interactive data dashboards. Manage and optimize large datasets using platforms like Snowflake, Teradata, and SQL/NoSQL databases. Collaborate with business and technical teams to translate requirements into robust data engineering solutions. Guide junior data professionals and foster a culture of learning and innovation. Communicate analytical findings clearly to non-technical stakeholders. Stay current with the latest in data science, machine learning, cloud platforms, and big data technologies. Key Skills & Technologies Machine Learning & AI Techniques: Supervised & unsupervised learning, deep learning, neural networks Reinforcement learning, decision trees, random forests, clustering NLP, computer vision, GANs, transfer learning Data Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn, Plotly Programming Languages & Libraries: Python (essential), R, SQL TensorFlow, PyTorch, scikit-learn, pandas, NumPy, Keras, SciPy Databases & Data Management: Snowflake, Teradata, SQL/NoSQL, ETL, data lakes, data warehousing Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP) Big Data Technologies: Apache Spark, Hadoop

Data Scientist Location: Bengaluru Department: Global Strategic Services Data Science EMEA Type: Full-Time | Hybrid About Cognite Cognite is a global SaaS leader harnessing AI and data to solve complex business challenges across industries such as Oil & Gas, Chemicals, Pharma, Manufacturing, and Energy. Our flagship solutions include Cognite Atlas AI, an industrial agent workbench, and the Cognite Data Fusion (CDF) platform. Recognized as a 2022 Technology Innovation Leader and the 2024 Microsoft Energy and Resources Partner of the Year, Cognite is at the forefront of industrial digital transformation. Our Values Impact: We focus on meaningful results. Ownership: We take responsibility, foster inclusivity, and share success. Relentless: We pursue innovation with determination and resilience. Who You Are 3+ years of industry experience (or academic equivalent) in Oil & Gas, Manufacturing, or Power & Utilities, developing analytical solutions for production optimization, predictive maintenance, and related applications (e.g., well monitoring, event prediction, production planning). 1+ years serving as a domain expert on internal or customer projects. Proficient in Python and its data ecosystem (pandas, numpy), and ML libraries such as scikit-learn, Keras, etc. Skilled in data visualization tools like PowerBI, Grafana, Tableau, or web frameworks like Plotly Dash, Streamlit. Advocates for software best practices, including automated testing and documentation. Experienced with version control systems such as Git. Comfortable contributing to large-scale software projects. Pragmatic thinker able to balance short- and long-term tradeoffs. Trusted advisor on machine learning applications, with excellent communication skills for technical stakeholders and customers. Experienced mentor and quality assurer for junior team members. Cloud experience, including building streaming models and deploying serverless functions. Track record working across diverse industries. Eager to stay current with advances in generative AI and explore its practical applications for customers. Be part of a diverse global team with 70+ nationalities and a strong commitment to Diversity, Equality, and Inclusion (DEI). Work from our Bengaluru office (Rathi Legacy, Hoodi) in a modern hybrid environment. Benefit from a flat organizational structure with direct access to decision-makers. Collaborate on impactful, ambitious projects alongside talented professionals across industries. Engage with our community through internal HUBs and open conversations. Make an Impact Join Cognite and help transform industrial sectors by enabling better decisions through AI and data. We encourage candidates of all backgrounds to apply. If you re ready to grow and innovate with us, apply today!

Senior Data Scientist Location: Bengaluru Department: Global Strategic Services Data Science EMEA Employment Type: Full-Time | Hybrid About Cognite Cognite is a global SaaS pioneer leveraging AI and data to solve complex business challenges in industries such as Oil & Gas, Chemicals, Pharma, Manufacturing, and Energy. Our key products include Cognite Atlas AI, an industrial agent workbench, and the Cognite Data Fusion platform. We are recognized as a 2022 Technology Innovation Leader and 2024 Microsoft Energy and Resources Partner of the Year. Our Values Impact: Driving meaningful outcomes. Ownership: Taking responsibility beyond comfort zones with inclusivity. Relentless: Innovating with determination and resilience. About the Role As a Senior Data Scientist, you will work in cross-functional teams delivering AI- and physics-based solutions that optimize operations and support decision-making in heavy-asset industries like Oil & Gas, Power & Utilities, Renewables, and Manufacturing. You will engage with customers, lead solution scoping, design, deployment, and operationalization using Cognite s data platform. What You ll Do Lead design and development of machine learning and physics-based models for industrial problems. Collaborate with data scientists, engineers, solution architects, and project managers to deliver scalable solutions. Conduct workshops and advise customers on solution approaches and pitfalls. Build and deploy dashboards and visualizations for data-driven insights. Mentor junior team members and promote best software practices including testing and documentation. Contribute to production-grade deployments and cloud-native solutions. Stay updated with emerging GenAI technologies and integrate them into customer use cases. Who You Are 5+ years as a Data Scientist, preferably in Oil & Gas, Maintenance, or Manufacturing domains. 1+ years as a domain expert on projects involving customer engagement. Proficient in Python, ML libraries (scikit-learn, Keras), and data visualization tools (PowerBI, Grafana, Tableau, Plotly Dash, Streamlit). Advocate for software best practices: automated testing, documentation, and version control (Git). Experienced contributor to large software projects. Pragmatic with the ability to balance short- and long-term priorities. Effective communicator with strong stakeholder management skills. Experienced mentor and quality assurer for junior colleagues. Cloud experience with serverless functions and production deployments. Proven success working across diverse industries. Eager to explore and apply GenAI developments in practical solutions. Work in a diverse global community with 70+ nationalities and a strong DEI focus. Modern hybrid work environment based in Bengaluru (Rathi Legacy, Hoodi). Flat organizational structure with direct access to decision-makers. Opportunity to collaborate on ambitious projects across industries. Access to ongoing learning and a vibrant internal community (HUB). Make an Impact Cognite is driving the future of industrial data innovation. Join us to help industries become more efficient, sustainable, and digitally transformed. We welcome candidates from all backgrounds apply today to be part of our journey!

Data Scientist Experience: 5+ Years Location: Bangalore, Karnataka, India Job Type: Full Time Job Summary We are seeking an experienced Data Scientist with over 5 years of expertise to join our innovative team in Bangalore. The ideal candidate will have hands-on experience in advanced statistical methods, machine learning, and deep learning frameworks, combined with strong skills in deploying models at scale. Key Responsibilities Apply advanced Statistics and Operations Research methods to solve complex business problems. Develop and deploy predictive and machine learning models using frameworks such as PyTorch, TensorFlow, Keras, and XGBoost. Utilize data engineering and big data tools including PySpark, Databricks, and Flask for building scalable data solutions. Implement and fine-tune NLP models like RNN, LSTM, and attention-based architectures, leveraging pre-trained models from Stanford, IBM, Azure, and OpenAI. Design and optimize efficient SQL queries to extract data from large databases. Work with visualization tools like D3.js, Dash Plotly, and deploy interactive dashboards using Streamlit. Utilize graph databases such as Neo4j for complex data relationships. Manage version control with tools like GitHub or Bitbucket. Deploy machine learning models into production environments using MLOps practices on cloud platforms such as AWS or Azure. Required Skills 5+ years of professional experience as a Data Scientist or similar role. Strong foundation in statistics, machine learning, and deep learning techniques. Proficient in Python-based data science libraries and frameworks. Hands-on experience with cloud-based MLOps and deployment. Excellent SQL skills for data extraction and manipulation. Experience with version control systems and collaborative development. Familiarity with NLP techniques and modern pre-trained language models. Strong problem-solving and communication skills. Qualifications Any graduate degree in Computer Science, Statistics, Mathematics, Engineering, or related field. Join a forward-thinking company in Bangalore, where you will work with cutting-edge technologies to create impactful data-driven solutions. Grow your career in an environment that values innovation, diversity, and continuous learning.

Job/Position Summary: Data Engineer Responsibilities: Implement data pipelines that meet design and are efficient, scalable, and maintainable. Implement best practices including proper use of source control, participation in code reviews, data validation and testing. Timely deliveries while working on projects. Act as advisor/mentor and helps junior data engineers in their deliverables. Must Have Skills: Should have experience of at least 4+ years with Data Engineering. Strong experience of design, implementation and fine-tuning big data processing pipelines in production environment. Experience with big tools like Hadoop, Spark, Kafka, Hive, Databricks. Experience in programming at least one of with Python, Java, Scala, Shell Script. Experience with relational SQL and NO SQL databases like PostgresSQL, MYSQL, Cassandra etc. Experience with any data visualization tool (Plotly, Tableau, Power BI, Google Data Studio, Quick sight etc.). Good To Have Skills: Should have Basic Knowledge of CI/CD Pipeline. Experience in working on at least one Cloud (AWS or Azure or GCP). For AWS: - Experience with AWS Cloud services like EC2, S3, EMR, RDS, Athena, Glue, Lambda, EMR. For Azure: -Experience with Azure Cloud services like Azure Blob/Data Lake GEN2, Delta Lake, Databricks, Azure SQL, Azure DevOps, Azure Data Factory, Power BI. For GCP: - Experience with GCP Cloud services Big Query, Cloud Storage bucket, DataProc, Dataflow, Pub Sub, Cloud Function, Data Studio. Sound familiarity in Versioning tools (Git, SVN etc.). Experience Mentoring students is desirable. Knowledge of latest developments in Machine Learning, Deep Learning, Optimization in Automotive domain. Open minded approach to explore multiple algorithms to design optimal solution. History of contribution to articles/blogs/whitepapers etc. in Analytics. History of contribution to Open Source. Requirement: ESSENTIAL SKILLS /COMPETENCIES Data Engineering Hadoop Kafka CI/CD Cloud

Introduction: In this role, you will be responsible for extracting and visualizing data from large, complex datasets to identify key signals that will drive product performance improvements. This includes performing correlation analysis, identifying patterns, and engaging with key stakeholders to initiate further analysis. You will also provide feedback to design, fab, test, and diagnostic teams to drive product improvements and corrective actions. The position demands technical expertise in data analysis, statistical techniques, and the use of machine learning, along with strong skills in programming languages such as Python and SQL. You will play a key role in supporting IBM's microprocessor products through various stages of development, characterization, and diagnostics. Responsibilities: Data Extraction and Analysis: Extract and generate data sets for correlation analysis, identifying key signals and engaging relevant stakeholders for deeper analysis. Product Behavior Reporting: Standard reporting of product behaviors, including yield and performance metrics, to ensure alignment with target specifications. Diagnostic and Performance Optimization: Drive product performance and yield improvement by using data analysis techniques and algorithms. Feedback and Collaboration: Provide critical feedback to the design, fab, test, and diagnostic teams to enable corrective actions and improvements in the respective areas. Technology Characterization: Focus on product development, product requirements, product test and yield analysis to identify design-process sensitivities. Failure Analysis and Diagnostics: Root cause product failures and conduct product diagnostics to improve performance and reliability. Yield and Reliability Analysis: Optimize power-performance characteristics, conduct product qualification, and analyze circuit-limited yield and system-level dependencies. Required Education and Experience: Bachelor's Degree (required) in Electrical Engineering (EE), Computer Science (CS), or Data Science. Master's Degree (preferred) in a relevant field. Technical Expertise: Proficiency in Data Analysis: Experience applying statistical techniques and machine learning to analyze complex datasets. Advanced Programming Skills: Expertise in Python (especially data science libraries such as Pandas, Plotly, Scipy, Sklearn, etc.) and SQL for data analysis and manipulation. Java Knowledge: Familiarity with Java is a plus. Device Physics Knowledge: A strong understanding of CMOS operation, device physics, and hardware characterization. Semiconductor Process and Technology Knowledge: Demonstrated knowledge of semiconductor process, technology, reliability, and yield analysis, especially related to SRAM and processors. Wafer Test and Yield Modelling: Experience in wafer test and yield modeling is a plus. What We Offer: A dynamic and challenging role in an innovative and highly technical environment. The opportunity to contribute to the development and enhancement of industry-leading microprocessor products. Competitive compensation and benefits, including opportunities for skill development and career growth. A collaborative, cross-functional team atmosphere where your ideas and insights will drive the future of IBM products. About IBM: At IBM, we create products that power the world s most important industries. From cloud computing to AI, IBM's technologies shape the way businesses and people interact with technology, and our product characterization and data analytics team is at the heart of innovation. Join us to work on cutting-edge products, contribute to groundbreaking advancements in microprocessor technology, and help shape the future of IBM products. If you're passionate about product development, data analytics, and semiconductor technology, apply today to become a part of the IBM Infrastructure Team! Qualification : A Bachelors / Masters in EE/ CS / Data Science is required.

Job/Position Summary Responsibilities: Implement data pipelines that meet design and are efficient, scalable, and maintainable Implement best practices including proper use of source control, participation in code reviews, data validation and testing Timely deliveries while working on projects Act as advisor/mentor and helps junior data engineers in their deliverables Must Have Skills: Should have experience of at least 4+ years with Data Engineering Strong experience of design, implementation and fine-tuning big data processing pipelines in production environment Experience with big tools like Hadoop, Spark, Kafka, Hive, Databricks Experience in programming at least one of with Python, Java, Scala, Shell Script Experience with relational SQL and NO SQL databases like PostgresSQL, MYSQL, Cassandra etc. Experience with any data visualization tool (Plotly, Tableau, Power BI, Google Data Studio, Quick sight etc.) Good To Have Skills: Should have Basic Knowledge of CI/CD Pipeline Experience in working on at least one Cloud (AWS or Azure or GCP) For AWS: - Experience with AWS Cloud services like EC2, S3, EMR, RDS, Athena, Glue, Lambda, EMR For Azure: -Experience with Azure Cloud services like Azure Blob/Data Lake GEN2, Delta Lake, Databricks, Azure SQL, Azure DevOps, Azure Data Factory, Power BI For GCP: - Experience with GCP Cloud services Big Query, Cloud Storage bucket, DataProc, Dataflow, Pub Sub, Cloud Function, Data Studio Sound familiarity in Versioning tools (Git, SVN etc.) Experience Mentoring students is desirable Knowledge of latest developments in Machine Learning, Deep Learning, Optimization in Automotive domain. Open minded approach to explore multiple algorithms to design optimal solution. History of contribution to articles/blogs/whitepapers etc. in Analytics History of contribution to Open Source. Requirement ESSENTIAL SKILLS /COMPETENCIES Data Engineering Hadoop Kafka CI/CD Cloud