Applied Data Scientist

Applied Data Scientist / Analytics Engineer Experience: 3-5 years in Data Science, Machine Learning, or Analytics. Strong experience with Python and SQL . Hands-on experience in Machine Learning model development . Perform Exploratory Data Analysis (EDA) on enterprise datasets. Develop business KPIs and analytical datasets. Experience with Feature Engineering . Build Anomaly Detection and Time Series Forecasting models. Develop Risk Scoring and predictive analytics models. Strong understanding of Statistics and model evaluation. Experience deploying ML models to production . Track experiments using MLflow . Build Analytical APIs for model inference. Create dashboards using Power BI/Tableau (preferred). Monitor model performance and detect model drift . Work with messy, incomplete, and large-scale datasets. Collaborate with Data Engineers, ML Leads, and business stakeholders. Explain model outputs to non-technical users. Strong problem-solving and root cause analysis skills. Experience with Git and version control. Knowledge of REST APIs is preferred. Preferred domain experience: Power & Utilities, Smart Metering, SCADA/IoT, Banking Risk, Fraud Detection, Telecom, Manufacturing (not mandatory). Focus on building scalable, explainable, and production-ready ML solutions .