Job Description

Primary Skills

• Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio

Specialization

• Data Science Advanced: Senior AI/ML Engineer

Job requirements

• AI Architect
• Location: Plainsboro, NJ
• work Type: Hybrid with min 4 days onsite per week
• Key: Please focus on AI Architect profiles rather than Senior/Lead Data Scientist profiles and with a Pharma/Life Sciences background, with Snowflake Cortex as a good-to-have skill.
• Experience in Data Science, Machine Learning, Artificial Intelligence, or related fields, with strong proficiency in SQL and Python. (preferably SQL)
  Hands-on experience in data analysis, feature engineering, model development, evaluation, and deployment of machine learning solutions to solve business problems.
• Good understanding of Generative AI concepts, including Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and emerging AI frameworks and protocols such as MCP.
• Ability to work with structured and unstructured data, build scalable AI/ML solutions, and collaborate with cross-functional teams to translate business requirements into data-driven outcomes.
• Strong problem-solving, analytical, and communication skills, with a demonstrated willingness and enthusiasm to learn new technologies, tools, and emerging AI/ML trends in a fast-evolving landscape.

Preferred Qualifications

• Experience with Snowflake data platform; exposure to Snowflake AI capabilities and Cortex services will be an added advantage.
• Familiarity with MLOps, model deployment, monitoring, and AI application lifecycle management.
• Knowledge of data warehousing, data engineering concepts, and API integrations.
• Exposure to GenAI application development, vector databases, semantic search, and AI orchestration frameworks.
• With Lifesciences experience preferred
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