Key Responsibilities
Develop and implement machine learning models for classification, regression, forecasting, clustering, and predictive analytics.
Apply statistical and machine learning techniques to identify patterns, trends, and business opportunities from large and complex datasets.
Build and optimize models using algorithms such as XGBoost, Random Forest, Gradient Boosting, Logistic/Linear Regression, Decision Trees, and clustering techniques.
Perform data preprocessing, feature engineering, feature selection, and exploratory data analysis (EDA).
Evaluate model performance using appropriate metrics and techniques such as cross-validation, hyperparameter tuning, ROC-AUC, Precision, Recall, F1-score, RMSE, and MAE.
Translate business requirements into analytical and machine learning solutions.
Identify relevant data sources, assess data quality, and work with structured and unstructured datasets.
Conduct statistical analysis and hypothesis testing to support data-driven decision-making.
Interpret model outputs and communicate insights, assumptions,



and recommendations to both technical and non-technical stakeholders.
Collaborate with Data Engineers, Software Engineers, Product Managers, and business teams to productionize analytical solutions.
Monitor model performance and continuously improve models based on changing data and business requirements.
Stay current with emerging developments in machine learning, statistics, and AI.

Required Skills & Experience
Solid hands-on experience in Machine Learning and Statistical Modelling.
Solid understanding of supervised and unsupervised learning techniques.
Experience with:XGBoost, Random Forest, Linear & Logistic Regression, Decision Trees, Classification & Regression, Clustering algorithms such as K-Means and hierarchical clustering

Must have skills
Machine Learning
Statistical Modelling(XGBoost, Random Forest, regression, classification, clustering,)

📌 Data Scientist Ml Bengaluru
🏢 Affine Analytics
📍 Bengaluru