Data Scientist

Role Overview We are looking for a skilled Data Scientist with strong experience in Time Series Forecasting, Predictive Analytics, and Machine Learning to join a leading analytics consulting engagement. The ideal candidate will have hands-on expertise in developing and deploying forecasting models for business and operational use cases. Key Responsibilities ● Develop, validate, and deploy time series forecasting models for business and operational planning. ● Work on predictive analytics and demand forecasting projects. ● Build ML-driven solutions using statistical and machine learning techniques. ● Analyze large datasets and derive actionable business insights. ● Collaborate with stakeholders to understand business requirements and translate them into analytical solutions. ● Contribute to end-to-end model development lifecycle including feature engineering, model evaluation, deployment, and monitoring. ● Participate in client discussions and present analytical findings effectively. Required Skills ● Strong programming experience in: ○ Python ○ R ○ SQL / NoSQL ○ Spark ● Experience with Cloud Platforms: ○ AWS ○ Azure ○ GCP ● Hands-on experience in: ○ Time Series Forecasting ○ Predictive Analytics ○ Demand Planning ○ Statistical Modeling ● Experience with Python libraries/frameworks such as: ○ NumPy ○ Pandas ○ Scikit-learn ○ TensorFlow ○ BERT ○ Scrapy ● Strong understanding of: ○ Statistics ○ Hypothesis Testing ○ Machine Learning Algorithms Preferred Machine Learning Expertise ● Random Forest ● Neural Networks ● Decision Trees ● Logistic Regression ● K-Means Clustering ● Linear Regression ● PCA Domain Experience Experience in one or more of the following domains is preferred: ● Retail ● Banking ● Insurance ● Supply Chain / Demand Planning Qualifications ● 4–8 years of relevant industry experience. ● Strong communication and stakeholder management skills. ● Prior consulting/client-facing experience is preferred. ● Ability to work in a fast-paced analytics environment.