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.