Senior Data Scientist

About the role

The Data Intelligence & Analytics organization builds the core data platform and internal products that power decision-making across the company. We design and operate large-scale data systems, own the company’s data lake, ingestion infrastructure, and platform tooling, and develop end-to-end applications that transform complex datasets into fast, reliable, business-critical products used daily by go-to-market, product, and engineering teams.

Responsibilities

• Partner and align with business leaders, stakeholders, product managers and internal teams to understand the business and product challenges and goals and address them using predictive analytics in a globally distributed environment.
• Understand data landscape i.e tooling, tech stack, source systems etc. and work closely with the data engineering team to improve the data collection and quality.
• Understand business/product strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals.
• Strong audience focused presentation and storytelling skills focused on key takeaways in a crisp and concise manner.
• Define, implement, and train statistical, machine learning, deep learning and generative AI models.
• Use software engineering best practices to publish model scores/insights/learnings at scale within the company.
• Able to define and spot macro and micro levels trends with statistical significance on a regular basis and understand key drivers driving those trends.
• Active role in hiring, growing, and mentoring the data scientist team in Austin.

Requirements

• M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields.
• 5+ years of data scientist experience with proven industry experience in a large scale environment (PBs scale & globally distributed teams).
• Strong experience working with business functions such as Finance, Sales, and Marketing to build models and drive impactful business outcomes (eg: customer and revenue growth).
• 2+ years experience with a fast-growing SaaS business based company is preferred.
• Strong experience in scientific computing using Python.
• Experience with Spark, SQL, Tableau, Google Analytics, BigQuery (or any other Big data/Cloud equivalent) etc.
• Experience working with and processing structured, unstructured, and semi-structured data.
• Strong cross-functional collaboration experience with data engineering and data analysts teams within the function.
• Proven track record of applying data insights and machine learning in order to address business needs and drive revenue.
• Experience in hiring data scientists and establishing team best practices is preferred.