Responsible for designing evaluation frameworks, testing methodologies, and telemetry analysis for agentic systems, with working knowledge of LangChain and LangGraph to support and enhance engineering efforts
Build, validate, and optimize data models focused on generative AI and large language models
Create and refine methods to measure AI model and agent performance, quality, and impact
Collaborate with product and engineering teams to inform and support integration of AI solutions (e.g., Gemini, OpenAI, Azure AI)
Stay current on advances in data science, machine learning, and generative AI
Mentor junior data scientists and engineers
Communicate clearly with stakeholders, presenting insights and recommendations
Apply statistical, econometric, and machine learning methods to generate actionable insights and support decision-making
Identify, integrate, and leverage key data sources to enhance analytics
Develop scalable data structures and analytic products
Lead end-to-end analytics and modeling projects, including data gathering, feature engineering, model development, evaluation, and monitoring
Provide insights to encourage data-driven decision-making throughout the organization
Mentor teams on data science best practices and contribute thought leadership through blogs or articles
Develop and deliver training on analytics tools and data science techniques (e.g., Alteryx, Tableau)
Explore and apply new data science tools and methodologies to maintain innovation.

Bachelor's degree required; advanced degree (Master’s or Ph.D.) in Data Science, Statistics, Econometrics, Computer Science, or related field strongly preferred
7+ years of professional experience as a Data Scientist, preferably in a software or SaaS environment
Strong programming skills in Python and SQL, including familiarity with advanced analytics libraries and frameworks
Experience working within both traditional SDLC and agile development environments
Expertise in a wide array of statistical methods, econometrics, machine learning algorithms, artificial intelligence, and predictive analytics
Proven experience developing scalable analytic data strategies and robust analytic products
Proficiency with visualization tools such as Tableau and experience in business analytics platforms like Alteryx
Familiarity with data pipelines, ETL processes, cloud databases, data warehouses (e.g., Snowflake), and data lakes
Experience deploying analytics solutions in cloud environments (GCP, AWS & Azure)
Strong communication skills, with the ability to clearly articulate complex analytic concepts and results to business stakeholders
Excellent problem-solving and interpersonal skills, capable of independently managing multiple projects in a dynamic environment.

Lead Data Scientist

Key skills