Job Description:

About the Role

We are seeking a highly skilled and experienced Senior Data Scientist to join our advanced analytics and AI team. The ideal candidate will have strong expertise in developing and deploying machine learning and statistical models, with hands-on experience in regression, classification, neural networks, forecasting, predictive analytics, anomaly detection, and emerging AI technologies including Generative AI and Large Language Models (LLMs).

The candidate should possess strong problem-solving abilities, business acumen, and the capability to translate complex data into actionable insights. Experience working on cloud platforms, particularly Google Cloud Platform (GCP), will be an added advantage.

Key Responsibilities

Machine Learning & Advanced Analytics

• Design, develop, validate, and deploy machine learning and statistical models for business-critical applications.
• Build supervised and unsupervised learning models including:
  • Regression models
  • Classification models
  • Clustering algorithms
  • Neural network/deep learning models
• Develop predictive modeling solutions for customer behavior, risk scoring, demand forecasting, fraud detection, recommendation systems, and operational optimization.
• Build anomaly detection frameworks for identifying unusual patterns, fraud, operational deviations, or system failures.
• Design and implement forecasting models using time-series techniques for sales, inventory, demand, and operational planning.
• Work on AI/GenAI-driven use cases leveraging Large Language Models (LLMs), prompt engineering, and intelligent automation solutions.

Data Processing & Feature Engineering

• Work with large-scale structured and unstructured datasets.
• Perform exploratory data analysis (EDA), data cleaning, transformation, and feature engineering.
• Build scalable data pipelines and reusable ML workflows.
• Optimize model performance using hyperparameter tuning and model evaluation techniques.

Model Deployment & MLOps

• Collaborate with engineering teams to deploy ML models into production environments.
• Monitor model performance, drift, and retraining strategies.
• Implement model versioning, experimentation tracking, and automation workflows.

Collaboration & Stakeholder Management

• Partner with business stakeholders to understand business problems and convert them into analytical solutions.
• Present insights, findings, and recommendations to technical and non-technical audiences.
• Work cross-functionally with data engineers, product managers, business analysts, and software developers.

Required Qualifications

• Bachelor’s or Master’s degree in:
  • Computer Science
  • Data Science
  • Statistics
  • Mathematics
  • Engineering
  • Or related quantitative field
• 6–8 years of hands-on experience in Data Science, Machine Learning, or Advanced Analytics roles.
• Strong understanding of statistical analysis, machine learning algorithms, deep learning concepts, and exposure to GenAI/LLM-based solutions.