Data Scientist

Job Title: Data Scientist

Location:

Department:

Data Scientist

advanced machine learning models and AI-driven solutions

forecasting and workforce optimization

LLMs (Large Language Models) and agentic AI

Key Responsibilities

• Design, develop, and deploy scalable ML models for forecasting, optimization and NLP use cases.
• Lead the end-to-end lifecycle of data science projects: problem framing, data exploration, model building, evaluation, and deployment.
• Explore and implement LLM and agentic AI applications to drive innovation in customer experience and workforce productivity.
• Partner with data engineering teams to build robust data pipelines and ensure model reliability in production.
• Mentor and guide junior data scientists/analysts, providing code reviews, best practices, and technical direction.
• Work closely with product managers and business teams to translate business needs into data science solutions.
• Communicate complex findings to non-technical stakeholders through visualizations, dashboards, and storytelling.
• Stay ahead of the curve with latest research and tools in ML/AI and recommend adoption where relevant.
  

Required Skills & Qualifications

• 5+ years of experience in data science or applied machine learning (retail/e-commerce experience preferred).
• Advanced proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
• Strong background in ML algorithms, time series forecasting, optimization, and statistics.
• Expertise in SQL and experience with large-scale data processing frameworks (Spark, PySpark, or similar).
• Proven experience in taking ML models from concept to production deployment.
• Strong problem-solving skills, ability to work with ambiguity, and experience in cross-functional collaboration.
• Excellent communication and stakeholder management skills.
  

Preferred Skills (Nice To Have)

• Hands-on experience with LLMs (OpenAI, HuggingFace, LangChain, RAG pipelines).
• Experience with agentic AI frameworks and multi-agent systems.
• Familiarity with cloud platforms (Azure, AWS, or GCP) and MLOps practices.
• Knowledge of optimization solvers (OR-Tools, Gurobi, CPLEX) for scheduling/resource allocation.