Our client is currently seeking a seasoned individual contributor with a strong background in Large Language Models (LLM) and Generative AI to join our recently established Data Science Lab. In this role, you will be instrumental in crafting advanced data science solutions that leverage the capabilities of machine learning and artificial intelligence, driving innovation across diverse business lines and products at the enterprise level. Collaborating closely with Data Science Tech Leads, you will actively contribute to impactful and highly visible projects, delivering AI/ML solutions that undergo rigorous market testing and deployment, thereby influencing risk management and overall financial performance. Successful candidates will bring industry-specific expertise, a genuine enthusiasm for applying state-of-the-art ML and AI insights, and the ability to design and implement data science capabilities that promote growth, competitive advantage, and customer satisfaction.
Deep Learning, Large Language Models (LLM), and Generative AI:
- Extract insights from unstructured data, including insurance contracts, medical records, sales notes, and customer servicing logs.
- Implement AI/ML solutions, enhancing underwriting risk assessment, claims auto adjudication, and customer servicing.
- Conduct large-scale experiments, covering unsupervised pre-training, fine-tuning, retrieval augmentation, and prompt engineering.
- Scale LLM models in both development and production environments.
- Design and create high-quality prompts and templates guiding LLM behavior, ensuring accuracy, relevance, and language fluency. Optimize prompts for improved user interactions and system performance.
- Evaluate LLM models using statistical tests, business metrics, and assessments of bias and other regulatory considerations.
Develop Enterprise Test and Learn Capabilities:
- Investigate current experimentation practices and causal inferencing/ML techniques, identifying opportunities for upscaling methodology best practices.
- Develop and execute advanced data-driven experiments to optimize various aspects of business operations.
- Create test hypotheses, design experiments including KPI selection, and collect and analyze data.
Support and Contribute to Building the Data Science Lab (DSL):
- Assist in use case development, including initial data exploration, project/sample design, data reception and processing, analysis, modeling, and the creation of final reports/presentations.
- Perform data wrangling, data matching, and ETL processes to explore diverse data sources, gain data expertise, conduct summary analyses, and prepare modeling datasets.
- Apply advanced statistical and AI/ML techniques to develop high-performing predictive models and conduct creative analyses to address business objectives and partner needs.
- Identify source data and perform data quality checks in both model/solution development and production.
- Collaborate with Data Engineers and MLOps in packaging and deploying models/solutions.
Contribute to the Overall Data Science Organization:
- Collaborate with cross-functional teams, including Data Science, Data Engineering, and Business groups.
- Contribute to the standardization of Data Science tools, processes, and best practices.
Who You Are:
You have a strong passion for staying at the forefront of technology and are enthusiastic about applying the latest AI/ML algorithms and methodologies.
You are characterized by analytical rigor, intellectual curiosity, and a proven track record of leading the creation and execution of data and analytic solutions to address complex business challenges.
Your satisfaction comes from collaborating with fellow data scientists to tackle challenging problems using AI/ML, and witnessing the successful deployment of solutions in the market, delivering tangible value to the company.
You thrive in working within a multi-disciplinary team, engaging with data engineers, business analysts, software developers, and functional business experts, as well as collaborating with business leaders.
What you will have:
PhD with a minimum of 2 years of experience, or Master's degree with at least 4 years of experience in Statistics, Computer Science, Engineering, Applied Mathematics, or a related field.
- Possess a minimum of 3 years of hands-on experience in ML modeling and development.
- Demonstrate strong theoretical foundations in probability and statistics, along with expertise in causal inferencing techniques.
- Showcase extensive experience in deep learning models, including Large Language Models (LLM) and Natural Language Processing (NLP).
- Have practical experience with GPU, distributed computing, and the application of parallelism to ML solutions.
- Exhibit strong programming skills in Python, particularly in PyTorch and/or Tensorflow.
- Maintain a solid background in algorithms and a diverse range of ML models.
- Display excellent communication skills and the ability to collaborate cross-functionally with Product, Engineering, and other teams at both leadership and hands-on levels.
- Possess outstanding analytical and problem-solving abilities, coupled with meticulous attention to detail.
- Demonstrate proven leadership through providing technical guidance and mentorship to data scientists, as well as strong management skills for monitoring and tracking performance, contributing to enterprise success.
- 2-3 Days a week at their NYC location
- Up to $180,000 per year