New York, New York
Director of Data Science (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 Director of Data Science to join the business and own the creation & expansion 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 leader to join and help them take this next step.
- Establish and oversee a generative AI practice, encompassing use case development and effective stakeholder management across multiple business domains. This responsibility extends to nurturing talent through the recruitment and training of data scientists, collaborating with ML Ops and IT to enhance infrastructure and tooling, educating stakeholders and the wider community, coordinating vendor selection and collaboration efforts, and ensuring compliance with model governance and legal requirements.
- Effectively coordinate diverse stakeholders throughout the solution design and project implementation phases, ensuring the successful creation and deployment of solutions in full production. In addition to technical leadership, this role emphasizes the significance of organizational effectiveness within a complex company, as well as the ability to craft compelling narratives and establish strong product branding.
- Leverage advanced statistical and AI techniques to develop high-performing predictive models and other solutions that effectively address business objectives and client requirements. Constantly explores and evaluates new statistical and machine learning analysis methods, software tools, and data sources to drive ongoing enhancement and refinement of quantitative solutions.
- Collaborate closely with technology and ML Ops teams to successfully deploy analytical models into production. Implements a seamless integration of the models by leveraging effective communication and coordination. Additionally, utilizes data visualization tools to conduct comprehensive model testing, exhibit modeling results, and highlight data patterns. Designs and establishes performance metrics for meticulous model selection and continuous performance monitoring.
- Effectively manage, nurture, and retain a talented team of highly skilled data scientists. This includes setting clear goals, conducting performance evaluations, optimizing resource allocation, and facilitating career and skill development opportunities. Additionally, responsible for hiring exceptional talent and providing comprehensive training to support the team’s professional growth and success.
- Engages in thorough exploration, design, and development of new and valuable data science use cases, while actively seeking buy-in from relevant stakeholders. Creates a strategic roadmap and establishes a robust project pipeline to guide the implementation of these use cases. Given the substantial size and complexity of the organization, numerous opportunities exist for identifying and pursuing impactful initiatives. Successful development of new use cases can lead to further expansion and growth of the team within this role.
- A postgraduate degree with a specialization in a quantitative discipline such as statistics, computer science, mathematics, economics, or a related field.
- 7+ 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).
- 3+ years of direct people management experience, successfully overseeing and developing technical teams while effectively recruiting and retaining top talent. Proven ability to adeptly manage both personal and team schedules, efficiently handling multiple time-sensitive projects and navigating competing priorities within a dynamic business environment. Maintaining strong and productive relationships with internal stakeholders and external partners is a consistent strength. Capable of providing valuable technical guidance and support to direct reports, ensuring their professional growth, and fostering a collaborative work environment.
- 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.
- 2 years 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.
Compensation is commensurate on experience ranging from roughly $200-250k on the base salary.