GenAI Data Scientist

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do Become a key player shaping Docusign's intelligent agreement platform. You'll apply and implement cutting-edge machine learning and Generative AI solutions, partnering with product and engineering to drive data-first strategies. Your work will involve prototyping and deploying novel GenAI applications to unlock critical business insights. This position is an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Lead the design and build of autonomous Agentic systems and workflows, collaborating with product, engineering, and go-to-market teams for at-scale campaigns Experiment with and implement advanced DL/ML models, with a primary focus on Agentic Frameworks, LLMs, and GenAI to predict user behavior, enhance product features, and drive automation Act as an Agentic AI expert, providing guidance and mentorship to other data scientists and team members Utilize prompt engineering, RAG, and model fine-tuning to derive actionable insights, generate content, and create novel user experiences Analyze customer data, market trends, and user insights to inform the development of GenAI solutions Partner with product teams to design, run, and analyze A/B and multivariate tests for GenAI features Present actionable insights on model performance and business potential, translating complex GenAI concepts for diverse stakeholders Stay updated on Generative AI advancements and propose new applications to solve business problems Drive projects to completion, proactively identifying and resolving roadblocks with cross-functional partners Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience building data science applications and ML pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and development, including common GenAI libraries Demonstrable experience designing, building, or implementing Agentic AI systems or multi-agent frameworks Strong knowledge of ML/DL/statistics concepts, including LLMs, transformer architectures, and their applications Experience with prompt engineering and utilizing pre-trained LLMs (APIs or open-source) Experience with large datasets, distributed computing, and cloud platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience training, evaluating, and deploying ML models in production (MLOps for GenAI) Proven track record contributing to ML/GenAI projects from ideation to deployment Experience with ML algorithms (e.g., CatBoost, XGBoost, LGBM) for classification/regression and understanding how they complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with a focus on AI-driven features Preferred Master's degree in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Experience applying data science and GenAI to customer success, product, or UX optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Hands-on experience with agentic frameworks like crewAI or similar platforms (e.g., LangChain, AutoGen) Familiarity with MLOps/data engineering tools; specific experience with MLflow, Airflow (DAGs), and Amazon SageMaker Experience with agile/SDLC, especially for AI products Experience with Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI-related work Ability to explain complex technical (including GenAI) concepts to diverse audiences Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at for assistance. Applicant and Candidate Privacy Notice #LI-Hybrid #LI-SA4Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience building data science applications and ML pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and development, including common GenAI libraries Demonstrable experience designing, building, or implementing Agentic AI systems or multi-agent frameworks Strong knowledge of ML/DL/statistics concepts, including LLMs, transformer architectures, and their applications Experience with prompt engineering and utilizing pre-trained LLMs (APIs or open-source) Experience with large datasets, distributed computing, and cloud platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience training, evaluating, and deploying ML models in production (MLOps for GenAI) Proven track record contributing to ML/GenAI projects from ideation to deployment Experience with ML algorithms (e.g., CatBoost, XGBoost, LGBM) for classification/regression and understanding how they complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with a focus on AI-driven features Preferred Master's degree in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Experience applying data science and GenAI to customer success, product, or UX optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Hands-on experience with agentic frameworks like crewAI or similar platforms (e.g., LangChain, AutoGen) Familiarity with MLOps/data engineering tools; specific experience with MLflow, Airflow (DAGs), and Amazon SageMaker Experience with agile/SDLC, especially for AI products Experience with Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI-related work Ability to explain complex technical (including GenAI) concepts to diverse audiencesBecome a key player shaping Docusign's intelligent agreement platform. You'll apply and implement cutting-edge machine learning and Generative AI solutions, partnering with product and engineering to drive data-first strategies. Your work will involve prototyping and deploying novel GenAI applications to unlock critical business insights. This position is an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Lead the design and build of autonomous Agentic systems and workflows, collaborating with product, engineering, and go-to-market teams for at-scale campaigns Experiment with and implement advanced DL/ML models, with a primary focus on Agentic Frameworks, LLMs, and GenAI to predict user behavior, enhance product features, and drive automation Act as an Agentic AI expert, providing guidance and mentorship to other data scientists and team members Utilize prompt engineering, RAG, and model fine-tuning to derive actionable insights, generate content, and create novel user experiences Analyze customer data, market trends, and user insights to inform the development of GenAI solutions Partner with product teams to design, run, and analyze A/B and multivariate tests for GenAI features Present actionable insights on model performance and business potential, translating complex GenAI concepts for diverse stakeholders Stay updated on Generative AI advancements and propose new applications to solve business problems Drive projects to completion, proactively identifying and resolving roadblocks with cross-functional partners