Capco
Financial Services
DataScientist–TimeSeries,StatisticalModelling&AzureDataBricks
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist – Time Series, Statistical Modelling & Azure Data Bricks at Capco. Skills: Statistical Forecasting, Time-Series Modelling, Geospatial Analytics, Model Explainability. Perform advanced data analysis. Perform feature engineering”
Industry & Context.
Data-driven decision making
What They're Looking For.
Must Have
Python, Statistical Modelling, Forecasting, Machine Learning, Time-series forecasting, Geospatial analytics, Model interpretation, Large-scale data analysis, Python, SQL, Databricks, Azure Data & Analytics ecosystem, Spark / PySpark
Nice to Have
Geospatial data analysis and modelling, GeoPandas, Shapely or similar libraries, Energy / Utilities domain experience, Forecasting, optimization, or operational analytics use cases, Azure ML / MLOps, SHAP, LIME, or similar Explainable AI frameworks
What You'll Do.
Perform advanced data analysis
Perform feature engineering
Perform exploratory analytics using Python
Develop predictive models
Validate predictive models
Deploy predictive models
Develop machine learning models
Validate machine learning models
Deploy machine learning models
Design statistical forecasting models
Implement statistical forecasting models
Design time-series models
Implement time-series models
Build geospatial analytics solutions
Build location-based modelling solutions
Apply model explainability techniques
Communicate insights to business stakeholders
Develop scalable analytical solutions using Databricks
Develop scalable analytical solutions using Azure
Collaborate with business teams
Collaborate with technical teams
Translate requirements into analytical solutions
Ensure data governance
Ensure data validation throughout model lifecycle
Contribute to reusable analytical frameworks
Contribute to reusable analytical standards
Contribute to reusable analytical best practices
How You'll Work.
Team & Collaboration
Business and technical teams
Communication Scope
Communicate insights
Full Job Description
Job Title: Data Scientist – 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 – 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 pre
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