Clustering Jobs in Gurgaon

Position: Infrastructure Engineer - SQL, Oracle, Sybase Location: Gurgaon Department: IT / Infrastructure Employment Type: Full-Time Company: GSPANN Technologies Job Description: GSPANN is looking for a skilled Infrastructure Engineer with deep expertise in SQL, Oracle, and Sybase databases. The successful candidate will design, optimize, and maintain enterprise database environments ensuring high performance, robust security, and data integrity. Role and Responsibilities: Design, implement, and manage enterprise databases using MySQL, Oracle Database, and Sybase platforms. Optimize database performance by employing techniques such as indexing, partitioning, and query optimization. Troubleshoot and resolve query-related and performance issues to maintain smooth database operations. Implement database backup, recovery, and disaster recovery processes to safeguard data. Develop and maintain database security policies, managing user roles, permissions, and access controls. Collaborate with development teams to understand database requirements and deliver efficient solutions. Document database architectures, configurations, operational procedures, and technical protocols. Monitor database performance and scalability to ensure reliability and efficiency. Evaluate emerging database technologies and incorporate updates as needed. Provide guidance on process accountability, data monitoring, and exception handling to improve data quality. Work with cross-functional teams to optimize business processes through automation and simplification. Utilize data conversion tools and techniques to assist with data migration and transformation initiatives. Skills and Experience: Bachelor s or Master s degree in Computer Science, Information Technology, or a related discipline. Relevant certifications in Oracle, MySQL, or Sybase are preferred. 6 to 8 years of experience in infrastructure engineering with hands-on expertise in MySQL, Oracle, and Sybase databases. Strong SQL programming skills and deep understanding of database management system principles. Proven experience in query debugging, performance tuning, and troubleshooting. Excellent analytical, problem-solving, and communication skills. Familiarity with data migration and transformation processes and tools. Qualification : Bachelors or Masters degree in Computer Science, Information Technology, or a related discipline.

Job Title: Associate Data Scientist - Social Media Analytics About this Role: Join Gartner s Social Media Analytics team, where you will help generate actionable insights from social media and internal/external Gartner data. This role is perfect for someone passionate about learning new technologies, text analytics, and working with unstructured data. As an Associate Data Scientist, you'll analyze data, draw recommendations, and visualize insights for research, using NLP, Machine Learning, and Deep Learning techniques. You will work closely with stakeholders to optimize data mining and improve the accuracy of insights generated. What You ll Do: Execute High-Impact Data Science Projects: Translate research objectives into actionable data and facts using social media and Gartner's internal/external data. Ad-hoc Modeling and Analytical Insights: Provide modeling and analytical insights to inform strategic and operational initiatives. Analyze Unstructured Data: Use advanced data science techniques to analyze unstructured text data, identifying insights and patterns. Interpret and Apply Findings: Align findings with business objectives and translate them into actionable business insights. Solve Business Challenges: Leverage Data Science, ML, and NLP to address pressing business challenges. Stakeholder Interaction: Collaborate with internal and external stakeholders to refine and improve findings. Data Science Driven Initiatives: Drive initiatives with some guidance while building strong domain expertise. Multi-tasking & Agility: Handle different projects in a fast-paced environment with strict SLAs and tight turnaround times. What You ll Need: Education: A fresher with a Master's in Engineering, Computer Science, Computer Applications, Statistics, Mathematics, Applied Mathematics, or Data Science. Alternatively, a B.E./B.Tech + Masters in Advanced Analytics or Data Science. Experience: 1-3 years of hands-on AI/ML experience, especially in Text Mining, NLP, and text analytics. Technical Skills: Expertise in Python (Pandas, Numpy, scikit-learn), SQL, TensorFlow, and other data science tools. Familiarity with AWS/Azure environments for training, testing, or deploying models. Machine Learning & NLP Knowledge: Ability to train, fine-tune, or apply ML, Deep Learning, LLMs, and NLP models. In-depth knowledge of NLP concepts and application experience. Data Preparation Skills: Expertise in data cleaning, normalization, and preparation for model training or inference. Analytical Mindset: Strong ability to identify patterns in unstructured datasets and provide actionable insights. Communication Skills: Strong written and verbal communication with the ability to structure clear, concise, and meaningful communication. Critical Thinking & Problem-Solving: Strong analytical skills and the ability to think independently to solve complex problems. Eagerness to Learn: A passion for learning about new technologies in the IT industry, Data Science, and Machine Learning. Research Techniques Understanding: Robust understanding of primary and secondary research methods. What We Offer: Flexible Hybrid Work Environment: Flexibility to work virtually when productive and meet colleagues in person for engaging, purposeful collaboration. Professional Growth: Gartner offers world-class benefits, competitive compensation, and tremendous rewards for top performers. Inclusive Work Culture: Diverse teams from various backgrounds and an environment that values collaboration and team success. Recognition as a Top Workplace: Gartner is consistently recognized as a great place to work worldwide. Join Gartner and contribute to world-class insights while developing cutting-edge technologies in the data science domain. We offer opportunities to grow, thrive, and make an impact! Qualification : A fresher with a Master's in Engineering, Computer Science, Computer Applications, Statistics, Mathematics, Applied Mathematics, or Data Science. Alternatively, a B.E./B.Tech + Masters in Advanced Analytics or Data Science.

Senior Data Scientist | FinBox | Gurgaon Location: Gurgaon Experience: 6-8 Years About FinBox FinBox is a cutting-edge fintech company that is reshaping how financial services are provided to businesses and consumers. Since our launch in 2017, we ve developed some of the most innovative technologies in the financial services space, enabling lenders such as Banks, NBFCs, and large enterprises to create and launch credit products in just days. As a Series A-funded company, we are expanding globally with offices in India, Vietnam, Indonesia, and the Philippines. Our mission is to build the best-in-class infrastructure for lending products, helping financial services companies scale and launch credit programs that set new standards in the era of digital finance. We've helped our clients disburse billions of dollars in credit, covering a wide range of unsecured and secured products like personal loans, business loans, mortgages, and education loans. We ve made a significant impact, supporting over 100 companies and serving millions of customers every month. Why You Should Join FinBox: Innovative Environment: We foster a culture of creativity and experimentation, encouraging our team to push the boundaries of what s possible in fintech. Impactful Work: Your work will directly influence millions of lives by making credit more accessible to individuals and businesses. Growth Opportunities: As a Series A-funded startup, we offer numerous opportunities for professional development and career advancement. Collaborative Culture: Be part of a diverse, inclusive team of experts who are passionate about making a difference and supporting each other. Role Overview: As a Senior Data Scientist at FinBox, you will work at the intersection of data and business, helping to deliver impactful solutions in the lending space. You will be responsible for analyzing large datasets, extracting meaningful insights, and applying advanced data science techniques to improve products and drive business results. Key Responsibilities: Data Analysis & Insights Generation: Analyze big data to produce actionable insights that directly contribute to product improvements and business outcomes. Model Building & Experimentation: Develop and deploy algorithms to extract useful information from large datasets. Use statistical analysis and machine learning techniques to create predictive models. Data Visualization & Reporting: Create interactive dashboards and visualizations to help monitor key metrics and inform stakeholders. Automate report generation using data visualization tools. Collaborate with Teams: Work closely with business teams to translate customer requirements into problem definitions and develop algorithmic solutions to address business challenges. Data Processing & Pre-processing: Gather, clean, and preprocess relevant data for insight generation and model building. Present Complex Results: Distill complex analysis into simple, clear visualizations and explanations for stakeholders at all levels. Apply Data Science Techniques: Use techniques such as exploratory data analysis (EDA), regression analysis, decision trees, clustering, survival analysis, and more. Continuous Improvement: Apply iterative analytics to steer the continuous improvement of products and algorithms. Who You Are: Analytical Thinker: You have strong analytical skills and a passion for deriving actionable insights from complex data. Technical Proficiency: Proficient in Python, R, SQL, and Excel. Familiarity with AWS and Git is highly preferred. Data Science Knowledge: Solid understanding of statistical concepts, machine learning models, and algorithms. Knowledge of data science tools and techniques for large-scale data analysis. Data Visualization Expert: You can create clear and impactful visualizations to communicate findings effectively. Problem Solver: You thrive on tackling ambiguous problems and developing innovative solutions that directly impact the business. Collaborative: You enjoy working in a team environment and are able to translate technical concepts into business-friendly language for diverse audiences. Desired Qualifications: 6-8 years of experience in data science with a focus on machine learning and statistical modeling. Expertise in Python, R, SQL, and Excel for data analysis and visualization. Experience with AWS, Git, and other cloud-based technologies. Solid understanding of statistical concepts, machine learning algorithms, and model deployment. Experience with data visualization tools and creating dashboards. Ability to effectively communicate complex results to non-technical stakeholders. Innovative Culture: At FinBox, we love disruption and creativity. Here, you can take ownership and contribute ideas that directly impact our product and the industry. Global Impact: Work on high-impact projects with global customers, improving access to credit for millions. Career Growth: FinBox offers a fast-paced, dynamic environment where you can rapidly grow your career. Collaboration & Diversity: Join a team of talented, passionate people who value collaboration and diverse perspectives. If you re ready to make a real difference in fintech and enjoy solving complex problems with data science, apply now to be part of the FinBox team!

Principal Data Scientist | FinBox | Gurgaon Location: Gurgaon Experience: 8-11 Years About FinBox FinBox is at the forefront of transforming the financial services industry with our innovative technologies. Since our inception in 2017, we have empowered lenders, such as Banks, NBFCs, and large enterprises, to build and launch credit products quickly within days rather than months or years. As a Series A funded company, we re expanding globally with offices in India, Vietnam, Indonesia, and the Philippines. Our mission is to build world-class infrastructure for lending products, helping financial services companies scale and launch credit programs that set a new standard in digital finance. We've already helped our customers disburse billions of dollars in credit across unsecured and secured credit, including personal loans, working capital loans, business loans, mortgages, and education loans, impacting over 5 million customers every month. Why You Should Join FinBox: Innovative Environment: We cultivate creativity and experimentation. We want you to challenge the status quo and push boundaries in fintech. Impactful Work: Your contributions will have a direct, positive impact on millions of lives, making credit more accessible to individuals and businesses globally. Growth Opportunities: As a Series A-funded startup, FinBox provides tremendous opportunities for career development and professional growth. Collaborative Culture: Join a diverse, inclusive, and highly skilled team, all passionate about making a meaningful difference in the fintech world. Role Overview: As a Principal Data Scientist at FinBox, you will play a critical role in driving data science initiatives and shaping the direction of data-driven decision-making. You will leverage your deep expertise in machine learning and statistics to design and deploy predictive models, optimize algorithms, and lead experimentation processes that directly impact our products and business strategies. You will work closely with cross-functional teams to translate business requirements into data-driven solutions and collaborate on deploying models at scale. Key Responsibilities: Data Analytics & Insights: Analyze large, complex datasets to generate insights that drive business growth and measure the impact of business decisions. Model Development & Experimentation: Design, build, and deploy predictive models, using machine learning techniques such as regression, clustering, decision trees, and survival analysis. Algorithm Development: Optimize algorithms to process data efficiently, supporting better decision-making across the business. A/B Testing & Experimentation: Lead A/B testing and other experimentation methodologies to refine products and optimize business strategies. Data Visualization & Reporting: Create automated dashboards and reports using visualization tools like Tableau or Power BI to clearly communicate insights to stakeholders. End-to-End Data Processing: Manage the full lifecycle of data processing from gathering and cleaning data to creating models and deploying them in production. Stakeholder Collaboration: Collaborate with product, engineering, and business teams to translate business needs into data-driven solutions. Model Deployment: Ensure that machine learning models are effectively deployed at scale and optimized for real-time business applications. Who You Are: Experience: 8+ years of experience in data science, with a proven track record in the finance or fintech industry. Technical Expertise: Strong proficiency in Python, R, SQL, and Excel for data analysis, model development, and automation. Cloud & Version Control: Proficiency in AWS for cloud-based deployment and Git for version control. Advanced Data Science Skills: Expertise in statistical methods and machine learning techniques including regression, clustering, decision trees, bootstrapping, and survival analysis. Data Visualization: Extensive experience with data visualization tools like Tableau, Power BI, or open-source libraries (e.g., Matplotlib, Seaborn). Problem Solving & Communication: Strong problem-solving skills with the ability to distill complex models into actionable insights for business stakeholders. Deployment Experience: Experience in deploying and maintaining machine learning models at scale, focusing on automation, real-time analytics, and continuous improvement. Innovative Culture: Join a team that is dedicated to pushing the boundaries of what is possible in fintech, with an environment that fosters creativity and experimentation. Global Impact: Your work will directly influence the future of financial services, helping millions of customers access fair and accessible credit. Career Growth: As a growing startup, FinBox offers substantial opportunities for personal and professional growth. Collaborative Team: Work with a team of talented, driven professionals who believe in collaboration, inclusivity, and shared success.

Data Scientist | FinBox | Gurgaon Location: Gurgaon Experience: 3-6 Years About FinBox: Where Fintech Meets Fun! Welcome to FinBox, where technology, innovation, and creativity meet to revolutionize financial services. Since our inception in 2017, we've been on a mission to transform the lending industry by helping lenders like Banks, NBFCs, and enterprises launch credit products faster than ever before. As a Series A funded company, we are growing rapidly with offices in India, Vietnam, Indonesia, and the Philippines. Our vision is to build world-class infrastructure for lending products that help banks and financial services companies scale globally. We've already helped customers disburse billions of dollars in both unsecured and secured credit, and our solutions are used by over 100 companies, impacting over 5 million customers monthly. Innovative Environment: We encourage creativity and experimentation, pushing the boundaries of what's possible in fintech. Impactful Work: Your contributions will directly impact the lives of millions, making credit more accessible. Growth Opportunities: As a growing Series A startup, we offer ample opportunities for professional development. Collaborative Culture: Join a diverse and supportive team that values different perspectives. Creative Thinkers: We love people who challenge the norm and bring fresh, out-of-the-box ideas. Customer Heroes: We need those who understand customer needs and go above and beyond to deliver exceptional experiences. Team Players: If you thrive in a collaborative environment and believe in the power of "we," you'll fit right in. How You'll Contribute to Our Data Science Team: Analyze structured and unstructured data to derive meaningful insights. Support predictive model development and statistical analyses to guide product decisions. Build dashboards and visualizations to monitor and report key business metrics. Assist in data gathering, pre-processing, and cleaning to maintain high-quality datasets. Conduct exploratory data analysis and hypothesis testing to enable data-driven decision-making. Automate reports and develop clear, effective data visualizations. Document data processes and findings in a structured, presentable format. Collaborate with cross-functional teams to translate business needs into actionable data-driven solutions. Apply foundational machine learning techniques, including regression analysis, clustering, and decision trees. Who You Are: Experience: 3+ years in data science, analytics, or a related field. Technical Skills: Strong proficiency in Python/R, SQL, and Excel for data manipulation and analysis. Visualization: Experience with tools like Tableau, Power BI, or similar for data visualization. Additional Skills: Familiarity with AWS, Git, and version control practices is a plus. Knowledge: Understanding of statistical concepts and basic machine learning models. Mindset: Eagerness to learn, experiment, and grow in a fast-paced, dynamic startup environment.