About the Role :
We are seeking an experienced Data Scientist with strong expertise in Classic Machine Learning techniques to join our team. The ideal candidate will have a proven track record of designing, building, and deploying predictive / statistical models, with a deep understanding of algorithms such as regression, tree-based methods, boosting, clustering, and time-series forecasting. This role requires someone who can combine statistical rigor, machine learning expertise, and business acumen to generate actionable insights and solve complex problems.
Key Responsibilities :
Data Exploration & Analysis :
- Gather, clean, and analyze large datasets from multiple sources.
- Perform statistical analysis and hypothesis testing to identify trends, patterns, and relationships.
Model Development & Implementation :
Build, validate, and deploy models using Classic ML techniques :Regression : Linear, Logistic :
Tree-based & Ensemble Models : Random Forest, Gradient Boosting, XGBoost, LightGBMClustering & Unsupervised Learning : K-Means, Hierarchical ClusteringStatistical & Predictive Modelling for business use casesDevelop Time-Series Forecasting Models (ARIMA, SARIMA, Prophet, ETS, etc.) for demand, sales, or trend prediction.Performance Optimization :
Conduct feature engineering, model tuning, and hyperparameter optimization.Evaluate models using statistical metrics (AUC, RMSE, MAE, R- , Precision / Recall, etc.).Business Problem Solving :
Translate business problems into analytical frameworks.Provide data-driven recommendations to stakeholders for strategic and operational decisions.Collaboration & Deployment :
Work with data engineers to ensure scalable data pipelines.Collaborate with cross-functional teams (Product, Marketing, Operations, Engineering).Deploy models into production and monitor performance.Required Skills & Experience :
Education : Master's or Bachelor's in Computer Science, Statistics, Mathematics, Data Science, or related field.Experience : 7+ years in Data Science with a strong focus on Classic Machine Learning and Statistical Modelling.Technical Expertise :
Hands-on experience with algorithms : Logistic Regression, Linear Regression, Random Forest, Gradient Boosting, XGBoost, LightGBM, K-Means, ARIMA / SARIMA.Strong background in statistical analysis, hypothesis testing, and predictive modelling.Experience in time-series forecasting and trend analysis.Programming & Tools :
Proficiency in Python (NumPy, Pandas, Scikit-learn, Statsmodels, PyCaret, etc.) and / or R. SQL for data querying.Familiarity with big data platforms (Spark, Hadoop) is a plus.Exposure to cloud ML platforms (AWS Sagemaker, Azure ML, GCP Vertex AI) preferred.Other Skills :
Strong problem-solving, critical thinking, and communication skills.Ability to explain complex models and statistical results to non-technical stakeholders.Good to Have :
Exposure to deep learning concepts (not mandatory, but an added advantage).Experience in MLOps practices - CI / CD for ML, model monitoring, model drift detection.Knowledge of domain-specific applications (finance, healthcare, retail, supply chain).(ref : iimjobs.com)
