Senior Data Scientist ( 4 - 7 years experience )

**We are currently hiring for a senior-level position and are looking for immediate joiners only.

If you are interested, please send your updated resume to resume@volgainfotech.com along with details of your CTC, ECTC and notice period. Also please provide a brief of your experience on Predictive Analytics and Machine learning, including the total number of years of hands-on experience in these areas. **

About the Role

We are looking for a visionary Senior Data Scientist who excels in predictive analytics and machine learning. You will lead the design, development, deployment, and optimization of data-driven products that drive high business impact—such as forecasting the price/value of stocks, commodities, or consumer goods (e.g., apparel, retail).

This role is for someone who has successfully taken machine learning models from concept to production, iteratively improved them based on user feedback and real-world performance, and thrives on delivering measurable results.

Key Responsibilities

• End-to-End Product Ownership: Lead the development of predictive models from exploration and prototype to full-scale production deployment.

• Forecasting & Prediction: Build robust time-series and regression models to predict prices/values of financial assets, oil, apparel, and other commodities.

• Model Optimization: Continuously monitor and fine-tune models for accuracy, performance, and scalability using real-time data feedback.

• ML Ops & Deployment: Collaborate with engineering to ensure successful deployment and monitoring of models in production environments.

• Stakeholder Collaboration: Translate business problems into analytical frameworks, working closely with product, strategy, and business teams.

• Data Strategy: Define and manage pipelines and feature stores using structured and unstructured data sources.

• Mentorship: Guide and mentor junior data scientists and analysts in best practices and advanced modeling techniques.

Required Qualifications

• 4- 7 years of experience in data science, with a strong background in predictive analytics and machine learning.

• Proven experience building and scaling ML models in production environments (not just notebooks or PoCs).

• Deep expertise in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch).

• Strong knowledge of time-series forecasting, regression techniques, and feature engineering.

• Experience in domains such as finance, commodities, retail pricing, or demand prediction is highly preferred.

• Experience working with cloud platforms (AWS, GCP, or Azure) and tools like Airflow, Docker, and MLflow.

• Ability to define success metrics, conduct A/B tests, and iterate based on measurable KPIs.

• Excellent communication and storytelling skills with both technical and non-technical stakeholders.

• PreferredExperience with LLMs, deep learning, or hybrid modeling approaches.

• Familiarity with data privacy, compliance, and governance in production systems.

• Publications or thought leadership in applied machine learning or forecasting.