Senior Data Scientist​/AI Engineer

Senior Data Scientist / AI Engineer - Chicago, IL

Compensation: $160,000

The Senior Data Scientist / AI Engineer drives the design, development, deployment, and governance of advanced generative, recommender, and predictive AI models to deliver measurable business value. The role ensures performance, accuracy, and scalability of AI solutions while embracing the latest research in NLP, predictive analytics, and information retrieval, and fosters best practices in data science, MLOps, and AI governance.

• Act as a thought partner to AI and Product leadership to identify opportunities where AI and machine learning can unlock business value.
• Lead the end‑to‑end design, development, validation, testing, and deployment of scalable AI and machine learning solutions.
• Apply advanced statistical analysis to generate actionable insights, identify trends, and measure model and business performance.
• Design and execute A/B testing frameworks to evaluate model quality and integrate insights into business processes.
• Collaborate cross‑functionally with engineering, product, analytics, and business teams to implement models, design monitoring tools, and ensure data quality.
• Drive AI research and development initiatives to ensure continued innovation and adoption of best‑in‑class AI methodologies.
• Monitor and analyze model performance, data integrity, and system reliability in production environments.

• Master’s or PhD in Computer Science, Electronics, Mathematics, Statistics, Economics, or a related technical discipline (or equivalent experience).

• 5+ years of hands‑on experience designing and deploying complex AI/ML solutions, preferably in regulated or data‑intensive industries.
• Proven experience developing production‑grade machine learning systems from concept through deployment.

• Strong proficiency in Python and advanced analytics frameworks (pandas, Spark, scikit‑learn).
• Deep expertise in AI methodologies including Generative AI, Agentic AI, Deep Learning, NLP, Supervised and Reinforcement Learning
  .
• Experience with ML frameworks and libraries such as Tensor Flow, PyTorch, Lang Chain, Llama Index
  , or similar.
• Hands‑on experience with cloud‑based ML platforms (AWS Sage Maker, Azure Machine Learning) is a plus.
• Strong understanding of MLOps / LLMOps best practices, including model versioning, monitoring, and deployment pipelines.
• Experience merging and transforming large, complex internal and external datasets to support AI solutions.

Mid‑Senior level

Full‑time

Engineering and Information Technology

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