Lead Data Scientist - Gen AI

State Farm•Dunwoody, GA

4d•Hybrid

About The Position

State Farm is seeking Data Scientists with experience in deep learning with Computer Vision and Nature Language Processing (NLP) and GenAI to support the growing demand for data science solutions across the organization. We are looking for talented, motivated individuals who will partner with business areas to help drive results for the enterprise via the development and adoption of AI/ML solutions. Applicants for this posting will be considered for Lead Data Scientist openings in Enterprise Technology – Data & AI. This area supports AI/ML solution development for Claims, Marketing, and other internal departments. It also hosts centers of excellence for natural language processing, experimental design, generative AI, & data science training/research. At State Farm, we believe in fostering professional growth and development. As a Lead Data Scientist at State Farm, you will have the opportunity to expand your analytic skill set across multiple development areas. Being a trustworthy consultant to business, you continue to develop and improve your communication skills as you explain technical concepts to your business partners. The diverse range of projects you will work on will refine your knowledge in AI/ML topics, software development practices, and tool development for department use. Data Science at State Farm: As a Data Scientist at State Farm, you will serve as a subject matter expert and consultant. In this role, you will share your knowledge and work to increase the use of analytics for decision-making across the organization. This opportunity affords consideration for data scientists who can bring in-demand skills and disciplines to our data science suites. Below are some of the tasks you can expect in the typical day of a Data Scientist: Develop and validate advanced deep learning models and GenAI solutions Provide input into and/or build datasets to support AI/ML solution development Collaborate with other team members on scoping solutions and project decision points Present on technical topics to peers, leadership, and other stakeholders, including non-technical business partners Lead/mentor other data scientists, interns, and other technical work teams Make strategic recommendations on data collection, integration, and retention requirements, incorporating business requirements and knowledge of best practices Serve as a peer reviewer to other model development teams Establish and leverage a network of associates with business domain and data expertise Instill a business-oriented mindset that delivers business outcomes for State Farm’s AI/ML portfolio Assess model performance, investigate changes, and perform model updates as necessary. Why Join Our Data Science Team? At State Farm, we are dedicated to helping our team members develop to their full potential. As a Data Scientist, you have the unique opportunity to develop both professionally & analytically. You will strengthen your communication skills through interactions with technical and non-technical business partners. Our Data Scientists also embrace staying current with the evolving data science landscape. The Selection Process: 1. After submitting your application, our recruitment team will carefully review your qualifications. If your profile aligns with our requirements, you will receive an invite to complete a video recording. 2. If selected to move forward, you will have the opportunity to participate in a live video interview with members of our hiring team. This interview focus on roleplaying interactions with a data science business partner and interpreting code and graphical outputs. 3. The next step is another live video interview with members of our hiring team. This interview will provide a chance for us to further assess your technical expertise and suitability for the role. 4. Following the successful completion of the Hiring Team round, competitive candidates may be invited to the final stage of the process: an in-person final loop interview. This round will involve interviews with members of our hiring panel, allowing us to gain deeper insights into your skills and experiences.

Requirements

Completed master’s or PhD in an analytical or engineering field such as statistics, computer science, mathematics, nature science (physics, chemistry etc.), economics, data science, quantitative marketing, operations research, industrial engineering, etc., with 3+ years of predictive model building experience
Experience with Python, deep learning frameworks (e.g., PyTorch), and fine-tuning open-source Computer Vision and NLP models
Experience with GenAI (e.g., LLM and Agentic AI) solution development
Experience in end-to-end ML models development for production (i.e., scoping project, design, ground truth collection, training, validation, and monitoring)
Experience with IDEs (e.g., IntelliJ, VS Code), Linux terminal, version control and cloud-based tools for ML development (e.g., AWS SageMaker)
Solid general coding practice and computer knowledge (e.g., latency vs throughput)
Strong communication skills and the ability to manage multiple, diverse stakeholders across business areas and leadership levels

Responsibilities

Develop and validate advanced deep learning models and GenAI solutions
Provide input into and/or build datasets to support AI/ML solution development
Collaborate with other team members on scoping solutions and project decision points
Present on technical topics to peers, leadership, and other stakeholders, including non-technical business partners
Lead/mentor other data scientists, interns, and other technical work teams
Make strategic recommendations on data collection, integration, and retention requirements, incorporating business requirements and knowledge of best practices
Serve as a peer reviewer to other model development teams
Establish and leverage a network of associates with business domain and data expertise
Instill a business-oriented mindset that delivers business outcomes for State Farm’s AI/ML portfolio
Assess model performance, investigate changes, and perform model updates as necessary.