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Data Scientist β Time Series, Statistical Modelling & Azure Data Bricks
Capco - Chennai, Tamil Nadu, India
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Capco - Chennai, Tamil Nadu, India
Data Scientist β Time Series, Statistical Modelling & Azure Data Bricks
Job Type: Not specified
Experience: Not specified
About Job
Job Title: Data Scientist β Time Series, Statistical Modelling & Azure Data Bricks About Us "Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. WHY JOIN CAPCO? You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry. MAKE AN IMPACT Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services. #BEYOURSELFATWORK Capco has a tolerant, open culture that values diversity, inclusivity, and creativity. CAREER ADVANCEMENT With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands. DIVERSITY & INCLUSION We believe that diversity of people and perspective gives us a competitive advantage. Job Description Data Scientist β Time Series, Statistical Modelling & Azure Data Bricks Job Summary We are seeking a Data Scientist with strong expertise in Python, Statistical Modelling, Forecasting, and Machine Learning to develop advanced analytics solutions using Azure and Databricks. The ideal candidate will have hands-on experience in time-series forecasting, geospatial analytics, model interpretation, and large-scale data analysis to support data-driven decision making. Key Responsibilities Perform advanced data analysis, feature engineering, and exploratory analytics using Python. Develop, validate, and deploy predictive and machine learning models. Design and implement statistical forecasting and time-series models. Build geospatial analytics and location-based modelling solutions. Apply model explainability techniques and communicate insights to business stakeholders. Develop scalable analytical solutions using Databricks and Azure. Collaborate with business and technical teams to translate requirements into analytical solutions. Ensure data quality, governance, and validation throughout the model lifecycle. Contribute to reusable analytical frameworks, standards, and best practices. Required Skills Data Science & Analytics Statistical Modelling and Forecasting Time-Series Analysis Machine Learning Model Explainability & Interpretation Feature Engineering Hypothesis Testing and Predictive Analytics Programming Python SQL Libraries Pandas NumPy Scikit-learn Statsmodels Prophet Scipy Geospatial Analytics Experience with geospatial data analysis and modelling GeoPandas, Shapely or similar libraries (preferred) Cloud & Platform Databricks Azure Data & Analytics ecosystem Spark / PySpark Preferred Experience Energy / Utilities domain experience Forecasting, optimization, or operational analytics use cases Experience communicating analytical insights to business stakeholders Good to Have Azure ML / MLOps SHAP, LIME, or similar Explainable AI frameworks Key hiring emphasis: Statistical Forecasting, Time-Series Modelling, Geospatial Analytics, Model Explainability, Python, SQL, Databricks. MLOps should be treated as a secondary / good-to-have capability rather than a primary screening criterion. If you are keen to join us, you will be part of an organization that values your contributions, recognizes your potential, and provides ample opportunities for growth. For more information, visit www.capco.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube. job perk: Posted At: 2 days ago, job perk: Schedule Type: Full-time
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