Data Scientist II

Role overview

Use statistical analysis, data mining, and machine learning to develop actionable insights and capabilities for product teams. You will partner with engineers, product managers, and business teams to identify opportunities, build data-driven solutions, and communicate findings that support product and business decisions.

Responsibilities - Analyze data using statistical and machine learning methods to surface useful, objective insights. - Work with product, sales, marketing, engineering, and data science partners to identify opportunities and shape data-driven solutions. - Develop or apply models that support product lines and business growth or engagement goals. - Explain analysis, recommendations, and results in clear written, verbal, and visual formats for senior stakeholders. - Adapt to changing priorities in a fast-moving environment.

Requirements - Bachelor’s degree in a quantitative field such as computer science, engineering, mathematics, statistics, or economics; a master’s degree is preferred. - At least 2 years of industry data science experience. - Strong statistical and machine learning foundations, including regression, classification, clustering, and offline or online model evaluation. - Experience with advanced methods such as supervised and unsupervised learning, graph algorithms, deep learning, recommendation systems, or generative AI. - Proficiency in Python and SQL, plus machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. - Experience with cloud services, preferably AWS, and workflow orchestration tools such as Airflow; strong communication and cross-functional collaboration skills.

Nice to have

Experience building LLM applications using prompting, retrieval-augmented generation, or evaluation; production machine learning systems; experimentation and A/B testing; or software engineering practices such as testing, CI/CD, Git, and shell scripting.