Data Scientist - Optimization and Advanced Machine Learning

• *Job Description**

Data Scientist - Optimization and Advanced Machine Learning
• *FM
• Johnston, RI
• On-site, Remote
• *Salary:

$103.04K - $148.10K/yr
• *Type:**

Full-time
• *Benefits:**

Medical, Retirement
• *Posted:**

3 hours ago
• *Job Description**

FM is seeking a Data Scientist specializing in optimization and advanced machine learning to translate business needs into analytical & AI solutions. The role involves designing, developing, and deploying optimization models, AI/ML algorithms, and decision‑support systems for real‑world problems across various teams.Key Responsibilities
• Build machine learning and AI solutions using Python/R and modern ML frameworks.
• Develop and deploy optimization models for risk assessment and operational decision‑making.
• Lead end‑to-end model development: problem framing, data processing, feature engineering, modeling, validation, implementation, and monitoring.
• Work with cross‑functional partners to translate analytical insights into business actions.
• Work with large‑scale datasets using SQL or similar tools and implement robust data pipelines.
• Apply creativity and domain expertise to evaluate and improve model performance and interpretability.
• Contribute to continuous innovation in optimization, ML, and AI practices across the organization.
• *Qualifications
• *Education:
• Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Data Science, or a related field. PhD preferred.
• *Experience
• 5+ years of industry experience in building optimization or machine learning solutions.
• 5+ years hands‑on experience with data processing, modeling, and advanced analytics using Python or R.
• 3+ years experience working with large datasets using SQL or similar technologies.
• Experience leading full‑cycle data science or optimization projects from ideation to deployment.
• Experience with cloud‑based analytics and machine learning platforms, preferably Azure Databricks
• *Technical Skills

Strong Knowledge & Practical Experience in
• Optimization methods:
• Linear / Non‑linear programming
• Mixed‑integer optimization
• Metaheuristics (GA, simulated annealing, evolutionary algorithms)
• Stochastic and robust optimization
• Core Machine Learning algorithms:
• Tree‑based models, gradient boosting
• Clustering & unsupervised learning
• Neural networks and deep learning fundamentals
• Simulation
• Model evaluation, validation, and experimentation
• Data wrangling, feature engineering, and pipeline design
• ML engineering practices following MLOps principles (model tracking, reproducibility, deployment)
• *Preferred Qualifications**
• Experience in risk management, insurance, or operations modeling.

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