Senior Data Scientist

Senior Data Scientist

Location: India (Remote)

Open Positions: 3

Experience: 5+ years in applied Data Science with production deployments

Technical Requirements

• Core Data Science & Statistics
• Statistical Foundation: Demonstrated experience with experimental design, A/B testing, causal inference, and time series analysis. Must be able to explain when and why to use different statistical tests.
• Machine Learning: Hands-on experience building and deploying models for regression, classification, clustering, and forecasting. Should have optimized hyperparameters, handled class imbalance, and dealt with feature drift in production.
• Deep Learning: Practical experience with neural networks beyond tutorials - custom architectures, loss functions, and optimization strategies for specific business problems.

Programming & Engineering

• Python Proficiency: Advanced usage of core data science stack (Pandas, NumPy, Scikit-learn). Experience with at least one deep learning framework (PyTorch preferred, TensorFlow acceptable).
• Production Code: Experience writing maintainable, tested code. Understanding of version control, code reviews, and collaborative development practices.
• Performance Optimization: Experience with profiling, vectorization, and handling datasets that don't fit in memory.

LLM Experience (Good to Have)

• API Integration: Experience integrating with OpenAI, Anthropic, or other LLM APIs in production applications.
• Prompt Engineering: Systematic approach to prompt design, few-shot learning, and prompt optimization for specific tasks.
• Fine-tuning & Customization: Experience with parameter-efficient fine-tuning (LoRA, QLoRA) or custom training for domain-specific applications.

Responsibilities

• Collect, clean, and analyze large datasets to derive insights and build predictive solutions.
• Design and deploy ML/DL models that solve business problems (customer insights, forecasting, optimization).
• Collaborate with cross-functional teams to integrate AI solutions into business workflows.
• Build dashboards, reports, and visualizations for business stakeholders.
• Contribute to projects involving LLM-based applications (chatbots, summarization, assistants) as needed.
• Stay updated with industry trends and contribute to knowledge sharing within the team.