Data Scientist (Machine Learning & Forecasting)

Job Description Data Scientist (Machine Learning & Forecasting) About the Role We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions. The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact. Key Responsibilities Design, develop, and deploy Machine Learning models for business-critical use cases. Build and optimize traditional ML models such as: Linear Regression Logistic Regression Decision Trees Random Forest Gradient Boosting (XGBoost, LightGBM, CatBoost) Support Vector Machines Clustering Algorithms Develop forecasting solutions using: ARIMA / SARIMA Prophet Exponential Smoothing Time-Series Regression Models Perform exploratory data analysis (EDA), feature engineering, and data validation. Evaluate model performance using appropriate statistical and business metrics. Work with structured and semi-structured datasets from multiple sources. Collaborate with business stakeholders to understand requirements and translate them into analytical solutions. Build scalable data pipelines and support model deployment in production environments. Monitor model performance, identify data drift, and implement model retraining strategies. Present insights and recommendations to technical and non-technical stakeholders. Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field. 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting. Technical Skills Machine Learning Strong understanding of supervised and unsupervised learning algorithms. Experience with ensemble methods and advanced ML techniques. Expertise in model selection, hyperparameter tuning, and performance optimization. Forecasting & Statistics Strong understanding of: Time-Series Analysis Forecasting Techniques Statistical Inference Hypothesis Testing Probability Distributions A/B Testing Programming Advanced proficiency in Python. Experience with: Pandas NumPy Scikit-learn Statsmodels XGBoost / LightGBM Prophet Data & SQL Strong SQL skills with experience in complex queries and performance optimization. Experience working with large-scale datasets. Visualization Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly. Cloud & MLOps (Preferred)Exposure to AWS, Azure, or GCP. Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices. Key Competencies Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities. Ability to work independently in a fast-paced environment. Strong business acumen and data-driven decision-making mindset. Job Description Data Scientist (Machine Learning & Forecasting) About the Role We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions. The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact. Key Responsibilities Design, develop, and deploy Machine Learning models for business-critical use cases. Build and optimize traditional ML models such as: Linear Regression Logistic Regression Decision Trees Random Forest Gradient Boosting (XGBoost, LightGBM, CatBoost) Support Vector Machines Clustering Algorithms Develop forecasting solutions using: ARIMA / SARIMA Prophet Exponential Smoothing Time-Series Regression Models Perform exploratory data analysis (EDA), feature engineering, and data validation. Evaluate model performance using appropriate statistical and business metrics. Work with structured and semi-structured datasets from multiple sources. Collaborate with business stakeholders to understand requirements and translate them into analytical solutions. Build scalable data pipelines and support model deployment in production environments. Monitor model performance, identify data drift, and implement model retraining strategies. Present insights and recommendations to technical and non-technical stakeholders. Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, Statistics,