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.
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