Sr. Data Scientist

Job Title:Senior Data Scientist
Job Summary

We are seeking an experienced Senior Data Scientist to lead end-to-end data science initiatives and develop innovative Machine Learning and Generative AI solutions. The ideal candidate will have strong expertise in data analytics, machine learning, large-scale data processing, and Generative AI technologies, with the ability to translate complex business challenges into actionable insights and scalable solutions.

Key Responsibilities

• Lead end-to-end data science projects, including data exploration, feature engineering, model development, validation, deployment, and ongoing support.
• Design, develop, and implement machine learning models to solve complex business problems.
• Collaborate with data engineering, product, and business teams to automate data science workflows and integrate models into enterprise platforms.
• Partner with stakeholders to identify opportunities where Data Science and Generative AI can drive operational excellence and business value.
• Develop scalable data pipelines using Python, PySpark, SQL, Pandas, and related technologies.
• Build and optimize predictive, prescriptive, and Generative AI models for business applications.
• Design and implement Retrieval-Augmented Generation (RAG) solutions for document search, summarization, and knowledge management.
• Fine-tune and evaluate Large Language Models (LLMs) for domain-specific use cases.
• Create compelling visualizations and presentations to communicate findings and recommendations to technical and non-technical audiences.

Required Qualifications

• experience in:
  • Data Science
  • Computer Science
  • Statistics
  • Operations Research
  • Applied Mathematics
  • Applied Physics
  • Related quantitative disciplines
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication and stakeholder management abilities.
• Experience working in Agile development environments.
• Ability to work independently and collaboratively in cross-functional teams.

Technical Skills

• hands-on experience processing, analyzing, and modeling large, complex datasets.
• experience with:
  • Python
  • SQL
  • PySpark
  • Pandas
  • Scala (preferred)
• experience across the full Machine Learning lifecycle:
  • Data preparation
  • Feature engineering
  • Model training
  • Validation
  • Deployment
  • Monitoring
• Strong knowledge of:
  • Machine Learning algorithms
  • Statistical modeling
  • Predictive analytics
  • Data visualization tools
• Experience with cloud platforms such as AWS, Azure, or GCP.

Generative AI Expertise

• Hands-on experience with Generative AI technologies and Large Language Models (LLMs).
• Experience building:
  • Retrieval-Augmented Generation (RAG) solutions
  • Semantic search applications
• Expertise in:
  • Prompt Engineering