Role:
The Data Scientist / Quant Developer will contribute to and help scale the growing project ecosystem within the Machine Learning – Predictive Data & Advanced Analytics team, with a strong emphasis on Generative AI.
The role requires deep quantitative and data science expertise combined with strong software engineering skills to design, prototype, and deploy scalable, cloud‑based analytics and AI solutions.
Key Responsibilities
- Design, develop, and deploy advanced data science and predictive analytics solutions, with a focus on Generative AI use cases
- Prototype and build custom analytics tools and data products using strong software development practices
- Work on end‑to‑end data science pipelines, including:
- Problem definition and scoping
- Data acquisition and preparation
- Exploratory data analysis (EDA)
- Model development and validation
- Insights generation, visualization, and storytelling
- Model deployment, monitoring, and maintenance
- Apply machine learning, data mining, NLP, and optimization techniques to correlate diverse datasets and extract business value
- Design and implement scalable, cloud‑based analytics architectures in collaboration with cross‑functional teams
- Work with streaming and batch data processing frameworks to support real‑time and large‑scale analytics
- Stay current with emerging technologies and best practices in Gen AI, ML, and advanced analytics, and apply them pragmatically to business problems
- Clearly articulate analytical findings, recommendations, and trade‑offs to both technical and non‑technical stakeholders
Required Skills & Experience
- Experience in Data Science, Quantitative Analytics, Predictive Analytics, or similar advanced analytical roles
- Strong software development background with the ability to prototype and productionize analytics solutions
- Hands‑on experience in data analysis and exploration across large and diverse datasets
- Experience with streaming and/or batch analytics frameworks (e.g., Kafka, Spark, Flink)
- Solid experience in machine learning, statistical modeling, optimization, and numerical methods
- Practical exposure to Generative AI, NLP, and modern ML techniques in real business applications
- Strong analytical thinking, learning agility, and the ability to work independently as well as collaboratively
- Proven ability to form insights, develop opinions, and clearly communicate them to the team
- Strong English communication skills (written and spoken)
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