Position: Applied Data Scientist

Experience: 3–5 Years

Relevant Experience: 3+ Years

Key Responsibilities

- Build, validate, deploy, and monitor machine learning models that support business decisions.
- Work extensively with Python and SQL for data extraction, analysis, modelling, and automation.
- Perform statistical analysis, exploratory analysis, root-cause analysis, segmentation, forecasting, and trend analysis.
- Develop supervised and unsupervised ML models including classification, propensity modelling, clustering, segmentation, and anomaly detection.
- Perform feature engineering and build reusable analytical/feature pipelines.
- Evaluate models using appropriate metrics such as precision, recall, calibration, and performance on imbalanced datasets.
- Monitor deployed models for data, feature, and model performance drift and support retraining/retuning.
- Create analytical datasets, business KPIs, data-quality checks, dashboards, and visualizations.




- Translate ambiguous business requirements into analytical problems, hypotheses, and measurable outcomes.
- Collaborate with business, product, data engineering, technology teams, and customers.
- Clearly communicate analytical findings, model methodology, limitations, and recommendations to technical and non-technical stakeholders.
- Mandatory Skill
- 3+ years of hands-on Applied Data Science / Decision Science
- Production ML model development and deployment
- Robust Python and SQL
- Machine Learning and Statistics
- Feature Engineering
- Scikit-learn
- XGBoost / LightGBM
- Model Evaluation and Validation
- Model Monitoring / Drift Detection
- Experience working directly with customers/stakeholders and customer data
- Ability to explain ML models and analytical findings to non-technical audiences

📌 Applied Data Scientist (Maharashtra)
🏢 Talentmatics
📍 Maharashtra