Senior Data Scientist

Job Description: Senior Data Scientist (Strong AI/ML Focus)

Role Overview

We are seeking a highly experienced Senior Data Scientist with 8–10 years of industry experience and strong AI/ML expertise to design, develop, and deliver advanced data science and machine learning solutions. This role blends deep statistical and analytical skills with hands-on AI/ML model development, driving both strategic insights and production-grade models.

The ideal candidate will work at the intersection of data, machine learning, and business—owning complex problem statements end to end and influencing decision-making at scale.

Key Responsibilities

• Lead end-to-end data science and AI/ML initiatives from problem formulation to deployment and impact measurement.
• Partner with business and product stakeholders to translate business challenges into data science and machine learning solutions.
• Perform deep exploration data analysis on large, complex datasets to uncover patterns, risks, and opportunities.
• Knowledge of AI integration over cloud platforms (e.g. GCP, Azure)
• Design, build, train, and evaluate machine learning models (supervised, unsupervised, and ensemble methods).
• Apply advanced techniques including RAG, LLMs. In addition, knowledge of graphDB (e.g. neo4j)
• Develop and evaluate experiments (A/B testing, causal inference, hypothesis testing) to guide decision-making.
• Collaborate closely with data engineers and ML engineers to productionize models and analytics pipelines.
• Ensure models meet standards for performance, scalability, explainability, and reliability.
• Monitor model performance and data drift; recommend retraining or enhancements as needed.
• Apply best practices for MLOps, including CI/CD for ML, model versioning, experiment tracking, and drift detection.
• Communicate insights, model results, and recommendations clearly to technical and senior business stakeholders.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field (PhD is a plus).
• 8–10 years of hands-on experience in data science with significant focus on AI/ML applications.
• Strong proficiency in Python and data science/ML libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, LangChain, Llamaindex or similar.
• Solid grounding in statistics, probability, and machine learning theory.
• Proven experience building, validating, and deploying ML models for real-world business use cases.
• Advanced SQL skills and experience working with large-scale datasets.
• Experience collaborating with engineering teams to operationalize models in production environments.
• Ability to independently own complex, ambiguous problem statements.

Preferred / Nice-to-Have Skills

• Experience with NLP.
• Exposure to Generative AI, LLMs, prompt engineering, or model fine-tuning.
• Familiarity with MLOps practices and tools (MLflow, Airflow, Docker, Kubernetes).
• Knowledge of model explainability, bias detection, and responsible AI practices.
• Experience working in regulated, risk-sensitive, or safety-critical domains.

Soft Skills

• Strong analytical and problem-solving mindset.
• Ability to influence decisions using data and clear storytelling.
• Leadership and mentorship capabilities.
• Effective communication with both technical and non-technical audiences.
• Proactive, curious, and outcome-oriented approach.