The demand for experienced Data Scientists continues to grow as organizations increasingly rely on Artificial Intelligence, Machine Learning, and Advanced Analytics to make strategic business decisions. If you have experience in Python, Statistical Modelling, Time-Series Forecasting, Machine Learning, SQL, and Cloud Analytics, then Capco has an exciting opportunity waiting for you.
Capco is currently hiring Data Scientists (3โ6 Years Experience) across Bengaluru, Chennai, Gurugram, Hyderabad, and Pune. This role offers the opportunity to work with modern AI technologies, enterprise-scale datasets, cloud-native analytics platforms, and global clients while solving complex business problems using advanced statistical and machine learning techniques.
๐ Job Details
๐ข Company: Capco
๐ผ Position: Data Scientist โ Time Series, Statistical Modelling
๐ Locations: Bengaluru, Chennai, Gurugram, Hyderabad, Pune
๐ป Experience: 3โ6 Years
๐ Job Type: Full-Time
๐ Domain: Data Science | Machine Learning | AI | Predictive Analytics
๐ข About Capco
Capco is a global technology and management consulting company that specializes in financial services, digital transformation, cloud engineering, data analytics, AI, and enterprise modernization.
Capco is recognized for its innovation-driven culture, collaborative work environment, continuous learning opportunities, and exposure to large-scale enterprise transformation projects. Employees work alongside highly skilled consultants, architects, engineers, and data scientists to build intelligent solutions that create measurable business value.
Some of the benefits of working at Capco include:
- ๐ Global client exposure
- ๐ Excellent career growth opportunities
- โ๏ธ Cloud-native AI projects
- ๐ค Machine Learning and Data Science innovation
- ๐ฏ Continuous learning and certification support
- ๐ค Collaborative engineering culture
- ๐ผ Enterprise-scale business challenges
- ๐ Exposure to emerging AI technologies
โญ Why This Role is Good for Experienced Professionals
This opportunity is perfect for professionals who already have experience in Data Science but want to work on larger enterprise projects using modern technologies.
Why you should consider this opportunity:
- ๐ Work on enterprise Machine Learning solutions.
- ๐ Build production-ready forecasting models.
- ๐ค Develop advanced predictive analytics solutions.
- โ๏ธ Gain hands-on exposure to Azure and Databricks.
- ๐ Work with Geospatial Analytics.
- ๐ Build scalable AI pipelines.
- ๐ง Learn Explainable AI techniques.
- ๐ป Collaborate with business stakeholders.
- ๐ Solve real-world business challenges.
- ๐ Expand your expertise in Time-Series Modelling and Statistical Forecasting.
๐ผ Key Responsibilities
As a Data Scientist at Capco, you’ll be responsible for:
- Performing exploratory data analysis using Python.
- Building advanced Machine Learning models.
- Developing Time-Series Forecasting solutions.
- Creating statistical prediction models.
- Designing feature engineering pipelines.
- Building Geospatial Analytics solutions.
- Implementing model explainability techniques.
- Working with Databricks and Azure platforms.
- Validating and monitoring ML models.
- Collaborating with business and engineering teams.
- Maintaining reusable analytical frameworks.
- Delivering actionable business insights.
๐ Skills Required
Capco is looking for candidates with expertise in the following technologies:
Programming
- Python
- SQL
Machine Learning
- Supervised Learning
- Unsupervised Learning
- Predictive Analytics
- Feature Engineering
- Model Evaluation
Statistical Analytics
- Statistical Modelling
- Time-Series Forecasting
- Hypothesis Testing
- Regression Analysis
Python Libraries
- Pandas
- NumPy
- Scikit-learn
- Statsmodels
- Prophet
- SciPy
Geospatial Analytics
- GeoPandas
- Shapely
Cloud Platforms
- Azure
- Databricks
- Spark
- PySpark
Explainable AI
- SHAP
- LIME
๐ฐ Expected Salary Range
Although Capco has not officially disclosed the salary, based on current market trends for similar roles in India, candidates can expect approximately:
| Experience | Expected CTC |
|---|---|
| 3 Years | โน12โ18 LPA |
| 4 Years | โน15โ22 LPA |
| 5 Years | โน20โ28 LPA |
| 6 Years | โน25โ35+ LPA |
Actual compensation depends on your technical expertise, interview performance, current salary, and location.
๐ Expected Interview Rounds
Most candidates can expect the following interview process:
- Resume Screening
- HR Discussion
- Technical Assessment
- Python Coding Round
- SQL Technical Interview
- Machine Learning Interview
- Statistical Modelling Discussion
- Time-Series Forecasting Round
- Azure / Databricks Technical Discussion
- Hiring Manager Interview
- HR & Salary Negotiation
Interview questions may cover:
- Python Programming
- SQL Queries
- Machine Learning Algorithms
- Feature Engineering
- Forecasting Models
- Time-Series Analysis
- Statistics
- Explainable AI
- Databricks
- Azure
- Spark
- Business Case Studies
๐ Preparation Tips
To improve your chances of getting selected:
- โ Practice Python coding every day.
- โ Revise SQL joins, window functions, and aggregations.
- โ Review Machine Learning fundamentals.
- โ Learn Time-Series Forecasting thoroughly.
- โ Practice Prophet and Statsmodels.
- โ Revise Feature Engineering techniques.
- โ Learn SHAP and LIME concepts.
- โ Understand Azure Data Science services.
- โ Practice Databricks notebooks.
- โ Learn Spark and PySpark basics.
- โ Build complete end-to-end ML projects.
- โ Solve business case studies.
- โ Revise statistical hypothesis testing.
- โ Prepare for behavioral interview questions.
๐ Resume Tips
Before applying, ensure your resume highlights:
- Python expertise
- SQL proficiency
- Machine Learning projects
- Time-Series Forecasting
- Statistical Modelling
- Predictive Analytics
- Azure or Databricks exposure
- Spark/PySpark projects
- Feature Engineering
- Explainable AI
- GitHub portfolio
- Kaggle projects (if available)
Whenever possible, quantify your achievements, for example:
- Increased forecasting accuracy by 22%.
- Reduced model execution time by 40%.
- Automated analytics pipelines handling millions of records.
- Improved prediction performance using feature engineering.
Recruiters prefer resumes with measurable business impact rather than generic project descriptions.
๐ Why You Should Apply
Capco offers an outstanding opportunity for experienced Data Scientists who want to work on enterprise-scale AI initiatives.
Some key advantages include:
- ๐ International consulting exposure
- โ๏ธ Azure & Databricks experience
- ๐ค Advanced AI & Machine Learning projects
- ๐ Enterprise analytics platforms
- ๐ Excellent career progression
- ๐ผ Global financial services clients
- ๐ Continuous learning culture
- ๐ง Exposure to Explainable AI and modern forecasting techniques
๐ฉ How to Apply?
๐ Application Link: Click Here
Before applying, update your resume to emphasize your experience with Python, SQL, Machine Learning, Statistical Modelling, Time-Series Forecasting, Azure, Databricks, Spark, and Explainable AI. A well-tailored resume that closely matches the job description significantly improves your chances of getting shortlisted for interviews.
