Lead Data Scientist (Generative AI)

Lead Data Scientist (Generative AI)
Our client is one of the most well-known, respected, and stable financial services organizations in the world. They are a perennial top player across a wide variety of business offerings. With nearly 200 years of history and an extensive pool of usable data, opportunities for high-impact data science and generative AI solutions to optimize the business are near limitless.

We are looking for a Lead Data Scientist to join and be one of the early members of their Generative AI practice. The centralized AI & Data practice has received significant backing from the C-Suite to grow its footprint. We are looking for an experienced Data Scientist to help them take this next step.

The Role:

• Contribute to and collaborate on building a generative AI practice. Responsibilities include supporting use case development, managing stakeholders, influencing infrastructure and tooling, educating stakeholders and the community, and participating in governance efforts.
• Effectively managing multiple stakeholders at equal levels throughout solution design and project execution to ensure the successful creation and deployment of solutions into full production.
• Take independent leadership in data analysis and modeling projects, encompassing all stages from project/sample design to business review meetings with internal and external clients to derive requirements and deliverables. Handles data reception and processing, conduct analyses and modeling, prepares final reports and presentations, communicates results effectively, and provides implementation support.
• Illustrate to both internal and external stakeholders the implementation of analytics to maximize business benefits. Offers comprehensive technical support, including strategic consulting, needs assessments, project scoping, and the preparation and presentation of analytical proposals.
• Leverage advanced statistical and AI techniques to develop high-performing predictive models and other solutions that effectively address business objectives and meet client needs. Conducts testing of new statistical and machine learning analysis methods, software tools, and data sources to continuously enhance the quality and effectiveness of quantitative solutions.
• Collaborate with technology and ML Ops teams to seamlessly implement analytical models into production. Utilizes data visualization tools to facilitate model testing and exhibit modeling results and data patterns. Designs and establishes performance metrics for model selection and ongoing performance monitoring.
• Apply data wrangling, data matching, and ETL (Extract, Transform, Load) techniques while programming in multiple languages to explore diverse data sources, develop a comprehensive understanding of the data, conduct summary analyses, and prepare datasets for modeling. Deploys analytical solutions effectively in production systems.

Technical Qualifications:

• A postgraduate degree with a specialization in a quantitative discipline such as statistics, computer science, mathematics, economics, or a related field.
• 3+ years of experience in predictive analytics, specifically working with large and intricate datasets. Demonstrating deep expertise in a wide range of statistical modeling techniques, including parametric methods such as linear regression, GLM (generalized linear models), survival analysis, time series analysis, as well as non-parametric techniques like GBM (gradient boosting machines), neural networks (NN), and natural language processing (NLP).
• Recent experience in the field of Natural Language Processing (NLP), including a strong understanding of foundational techniques and methodologies. Well-versed in working with large language models and transformer-based architectures, which are instrumental in advancing NLP tasks such as text classification, sentiment analysis, named entity recognition, machine translation, and more. Keeping up-to-date with the latest developments in NLP research and applying that knowledge to effectively solve real-world challenges.
• 1 year of hands-on experience in developing and deploying generative AI solutions. Proficient in all aspects of the development cycle, including training, fine-tuning, and prompt engineering. Skilled in harnessing generative AI techniques to create innovative and practical solutions that address specific business needs. Experienced in effectively integrating these solutions into existing systems and workflows, ensuring seamless deployment and integration for optimal performance.

Location: New York
Compensation is commensurate with experience, the base salary will be roughly $170-200k.
 

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