Data Scientist Deterministic Modelling

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

• Design, develop, and deploy end-to-end machine learning solutions using Python and Databricks.
• Build and optimize scalable data processing pipelines using PySpark and Spark.
• Perform data extraction, cleansing, transformation, and feature engineering on structured and unstructured datasets.
• Develop, evaluate, and implement traditional machine learning models for classification, regression, clustering, and prediction problems.
• Work extensively with Databricks notebooks, Jupyter Notebooks, and collaborative development environments.
• Develop reusable, production-ready ML workflows and analytical frameworks.
• Collaborate with data engineers and business stakeholders to understand business requirements and translate them into scalable analytical solutions.
• Optimize model performance through experimentation, hyperparameter tuning, and validation.
• Ensure data quality, governance, and best practices throughout the data and model lifecycle.
• Document methodologies, model performance, and technical solutions for knowledge sharing and maintainability.

Required Skills

Programming

• Python
• PySpark
• SQL

Data Science & Machine Learning

• Strong understanding of traditional Machine Learning algorithms
• Supervised and Unsupervised Learning
• Feature Engineering
• Model Evaluation and Validation
• Statistical Analysis
• Predictive Analytics
• Data Preprocessing and Transformation

Big Data & Data Processing

• Apache Spark
• PySpark
• Large-scale data processing
• Data pipeline development and optimization
• ETL/ELT concepts

Databricks

• Strong hands-on experience with Databricks
• Experience working with Databricks Notebooks
• Building scalable ML workflows in Databricks
• Delta Lake (preferred)
• Databricks Jobs and Workflows (preferred)

Python Libraries

• Pandas
• NumPy
• Scikit-learn
• SciPy
• Matplotlib / Seaborn
• MLflow (preferred)

Cloud & Platform

• Azure Databricks
• Azure Data Services (preferred)
• Azure Machine Learning (good to have)

Development Tools

• Jupyter Notebook
• Git
• CI/CD concepts for ML pipelines (preferred)

Good to Have

• Experience implementing MLOps pipelines using MLflow or Azure ML.
• Time-Series Forecasting using Statsmodels or Prophet.
• Explainable AI frameworks such as SHAP or LIME.
• Experience with orchestration tools such as Azure Data Factory or Apache Airflow.
• Experience with Delta Lake and Unity Catalog.
• Knowledge of Docker and containerized deployments.
• Experience working in Agile environments.

Preferred Experience

• 3+ years of experience in Data Science and Machine Learning.
• Strong experience implementing ML solutions on Databricks.
• Experience building production-grade data and ML pipelines using PySpark.
• Experience with Azure cloud ecosystem is preferred.
• Ability to communicate technical concepts and analytical insights to business stakeholders.
• Experience in Energy, Utilities, Manufacturing, or other data-intensive industries is an advantage

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.