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Lead Optimization Data Scientist
2 months ago
Lead Optimization Data Scientist
Location: London (Hybrid)
Compensation: £100,000 - £150,000 GBP + equity
We are seeking several data professionals, including a Lead Optimization Data Scientist, who will play a pivotal role in the integration of cloud technology, DevOps, and machine learning to develop and implement sophisticated optimization models across various sectors. Your knowledge will be instrumental in advancing our technological capabilities, enhancing our service offerings, and addressing intricate challenges at scale.
Key Responsibilities:
- Create Scalable Optimization Models: Engineer effective optimization frameworks that significantly enhance operational efficiency utilizing the latest advancements in machine learning and operations research.
- From Prototype to Implementation: Convert optimization model prototypes into fully functional, scalable applications that yield tangible business results.
- Generate Business Insights: Leverage optimization models to produce actionable insights that inform strategic decisions and communicate these effectively to stakeholders.
- Specialization in Optimization: Innovate advanced algorithms to tackle complex challenges in logistics, scheduling, resource distribution, and beyond.
- Maintain Data Quality: Perform comprehensive data evaluations to support effective optimization solutions.
Qualifications:
- Advanced Knowledge: Master’s degree (or equivalent) in Operations Research, Computer Science, Engineering, or a related discipline with a strong emphasis on optimization.
- Demonstrated Experience: 5-7+ years in quantitative analysis, data modeling, or operations research, with extensive knowledge of optimization methodologies.
- Technical Proficiency: Skilled in Python, SQL, and optimization frameworks (e.g., PuLP, Gurobi, CPLEX).
Preferred Qualifications:
- Leadership in Optimization: Experience overseeing complex optimization initiatives, guiding teams, and managing cross-departmental projects.
- Integration of Machine Learning: Proficiency in combining optimization with machine learning methodologies (e.g., TensorFlow, PyTorch).
- Cloud and MLOps Knowledge: Familiarity with deploying and managing models on cloud services (AWS, GCP, Azure) and utilizing MLOps tools (MLFlow, BentoML).
- Ethical AI Understanding: Solid grasp of AI ethics in optimization and a commitment to ongoing professional development.
This role offers a dynamic and progressive environment where you will collaborate with a highly skilled team of Data & AI experts.
