• Analyze complex scientific data using statistics, machine learning, and data science methods • Build and improve workflows for data ingestion, cleaning, feature extraction, modeling, and reporting • Develop AI-enabled tools or workflow automation to support repeatable scientific analysis tasks • Partner with scientists, engineers, and operations teams to solve practical lab data problems • Build, test, validate, and document predictive or classification models for scientific applications • Perform exploratory analysis to identify trends, anomalies, and relationships in experimental data • Support automation and standardization of data analysis and reporting processes • Communicate results clearly to both technical and non-technical stakeholders • Contribute to scalable, reproducible data workflows that improve lab efficiency

Role Description The Accelerator seeks a Data Scientist to bolster our data team and provide insight in the data we collect. This is a 6-month term role with potential for extension. - Work closely with the Accelerator leadership team to align data science initiatives with overarching goals and long-term vision. - Identify and prioritize development projects that benefit from data science methodologies and innovations. - Apply advanced statistical analysis, data mining, and machine learning techniques to analyze complex engineering datasets. - Design, develop, and optimize predictive models, simulations, and algorithms to solve key engineering and scientific challenges. - Drive the development and deployment of data-driven products and solutions, ensuring alignment with strategic goals. - Ensure the accuracy, integrity, and quality of data to be made available through the Accelerator. - Collaborate with data engineering teams to optimize data workflows, enhance data accessibility, and improve performance of modeling systems. - Understand the end-to-end data lifecycle and its effects on machine learning models, actively enhancing and optimizing data pipelines for improved model outcomes. - Develop data pipelines, automation systems, and scalable infrastructure for real-time and batch processing. - Work effectively in a modern, professional software and data engineering environment with a strong understanding of Agile concepts and practices. - Stay current with the latest advancements in data science, machine learning, and relevant engineering fields to continuously innovate. - Collaborate with research teams to apply state-of-the-art techniques to ongoing scientific challenges. - Build strong relationships with external partners, driving collaborations that enhance the Accelerator’s scientific impact. Qualifications - 3+ years of relevant work experience as a frontline data scientist, with a record of building innovative solutions. - Experience working in a remote, agile environment. - Bachelor's degree or equivalent in a relevant field. - Strong communication and interpersonal skills to effectively collaborate with researchers in the field, other engineers at various levels of experience, and administrative and leadership team members. Requirements - Background in engineering principles and familiarity with various engineering disciplines. - Publications in reputable scientific journals or conferences is desirable. Benefits - Comprehensive benefit program to eligible employees.

• Analyze large volumes of structured and unstructured data to generate insights and support decision-making; • Develop statistical models and Machine Learning solutions to solve complex problems; • Create data visualizations that communicate information clearly and effectively to diverse audiences; • Develop and maintain analyses and experiments using data science tools and libraries; • Collaborate with global teams, contributing to analytical initiatives and data-driven projects; • Apply software engineering best practices to ensure quality, reproducibility, and scalability of developed solutions; • Other related responsibilities.

• Lead and develop a team of Data Scientists and Analysts supporting Product, Marketing, Sales, and Customer Experience. • Lead behavioral analytics, customer segmentation, experimentation, and product measurement efforts, helping teams understand customer behavior, evaluate product performance, and prioritize roadmap investments. • Develop and maintain revenue forecasts, churn models, customer health scores, and account or opportunity scoring models used across the business. • Partner with our data engineering team to manage our internal agentic data analytics platform, Smarty, supporting self-serve data access and analytics. • Define standards and best practices for analytics and data science, and refine operational frameworks to drive efficiency and scale across the team.