Data Scientist Time Series, Statistical Modelling & Azure Data Bricks
- Capco
- 2 - 9 years
- Bengaluru
- 21 days ago
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Job Description
Job Title: 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 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.
Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.Job Classification
Industry: BankingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Full Stack Data ScientistEmployement Type: Full timeContact Details:
Company: CapcoLocation(s): Bengaluru
Keyskills: Data analysis data science Analytical Management consulting Data quality Forecasting Operations Analytics Financial services SQL
Capco
Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by c...
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