Responsibilities

• Partner with our clients' leadership teams, engineers, program managers, and data analysts to understand data needs.
• Identify, acquire, process, and explore relevant data sources.
• Analyze large amounts of structured and unstructured information to discover trends and patterns.
• Use your data analytics and data science expertise to derive valuable insights from datasets, and build predictive models and machine learning algorithms.
• Design, build, fine-tune, and deploy LLM-based systems using models such as GPT, Claude, Gemini, Llama, and Mistral.
• Develop GenAI-powered applications (self-managed and API-based) that meet real business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses).
• Design and optimize prompting strategies (few-shot, Chain/Tree-of-Thought, ReAct, self-reflection, guardrails) to improve reliability and control.
• Communicate at scale through multiple mediums: presentations, dashboards, datasets, bots, and more.
• Propose solutions and strategies to business challenges.
• Collaborate with engineering and product development teams.

Requirements

• Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field.
• 2+ years of experience as a Data Scientist or Data Analyst.
• Strong programming skills, particularly Python and SQL.
• Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.).
• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, etc.).
• Excellent communication skills, with the ability to explain complex technical concepts simply.

Preferred

• Experience building agentic AI systems.
• Good understanding of machine learning techniques.
• Good understanding of statistical techniques and concepts.
• Experience with data visualization tools.
• Experience developing conversational AI systems / chatbots.
• Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as the Model Context Protocol (MCP).
• Experience deploying models at scale in production environments.

Benefits

• Medical, dental, and vision; company-paid life and AD&D; voluntary supplemental insurance and EAP
• 401(k) with company match and immediate vesting; HSA and FSA options
• College savings and student loan repayment programs
• Paid parental leave; generous PTO, nine company holidays, and one floating holiday
• Cell phone stipend; well-being and professional development programs
• Benefits are subject to applicable plan terms and eligibility requirements.