Skills- Data science, Machine learning, Python, LLM, and generative AI

Detailed

- Translate workforce and HR business requirements into well-defined data science use cases and measurable outcomes. Prepare structured and unstructured data, engineer relevant features, and build reusable data pipelines using Python and SQL.
- Develop and enhance statistical, predictive, and machine learning models using appropriate algorithms and techniques.
- Design experiments and evaluate models for performance, stability, reliability, and business relevance.
- Conduct error analysis, interpret model outcomes, and identify opportunities for continuous model improvement
- Develop Generative AI and agent-based solutions to automate tasks, synthesize information, and augment data science workflows
- Communicate methodologies, assumptions, limitations, and outcomes clearly to business and technical stakeholders.
- Robust statistical fundamentals, including regression, hypothesis testing, sampling, feature selection, and model evaluation.
- Proficiency in Python 3.x for data preparation, feature engineering, statistical analysis, and machine learning, with working knowledge of SQL.
- Working knowledge of Generative AI tools, with foundational exposure to developing or working with AI agents.



Proficiency in Advanced Excel and a good understanding of HR data and workforce metrics.
- Hands-on experience using AI-assisted development tools such as Microsoft GitHub Copilot, Claude, or Codex, along with development environments such as Visual Studio Code.

Key Skills Mandatory Key Skills: Proficiency in Python, SQL, statistical analysis, machine learning, model development and validation, structured and unstructured data handling, Generative AI fundamentals, AI agents, Advanced Excel, and understanding of HR data and workforce metrics, along with robust problem-solving, communication, and collaboration skills.

Good to Have Skills:

Hands-on experience in classification, regression, clustering, NLP, time-series modelling, hyper parameter tuning, cross-validation, model explain ability, responsible AI, prompt engineering, RAG, agent-based workflows, AI-assisted development tools such as GitHub Copilot or Claude, VS Code, version control, and HR analytics use cases such as attrition prediction and talent analytics

Candidate Expectations

Candidate Location: Anywhere in India

Job Location: Pune, Hyderabad, Chennai, Bangalore, and Kolkata

📌 Analyst - Data scientist (Chennai)
🏢 Golden Opportunities
📍 Chennai