Senior Data Scientist
Hybrid
Posted 10d ago
Job Location
Hybrid
Tech Stack
Remote Work Policy
On-site
Categories
Applied AI Engineer
About the job
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. Our work sits at the intersection of data platforms, distributed systems, and product development, giving engineers the opportunity to own meaningful problems across the stack and build systems that truly run the business. You will focus on building scalable, reliable AI/ML models, services and GenAI powered application backends, partnering closely with data and full-stack engineers to deliver new features and operate the pipelines and platforms behind our products.
Responsibilities
- Partner with business leaders, stakeholders, and product managers to understand challenges and goals, and address them using predictive analytics.
- Understand the data landscape, including tooling and tech stack, and collaborate with data engineering to improve data collection and quality.
- Align analysis efforts with business/product strategy and high-level roadmaps to provide data insights and achieve strategic goals.
- Present key takeaways in a crisp and concise manner, tailored to the audience.
- Define, implement, and train statistical, machine learning, deep learning, and generative AI models.
- Apply software engineering best practices to publish model scores, insights, and learnings at scale.
- Regularly identify and analyze macro and micro trends with statistical significance and understand their driving factors.
- Actively participate in hiring, growing, and mentoring the data scientist team.
Requirements
- M.S. or Ph.D. in Computer Science, Statistics, Mathematics, or other quantitative fields.
- 5+ years of data scientist experience in a large-scale, globally distributed environment.
- Strong experience building models and driving business outcomes with functions like Finance, Sales, and Marketing.
- 2+ years of experience in a fast-growing SaaS business is preferred.
- Strong experience in scientific computing using Python.
- Experience with Spark, SQL, Tableau, Google Analytics, BigQuery, or similar big data/cloud technologies.
- Experience processing structured, unstructured, and semi-structured data.
- Strong cross-functional collaboration experience with data engineering and data analyst teams.
- Proven track record of applying data insights and machine learning to address business needs and drive revenue.
- Proficiency in large language models and frameworks like Langchain and Langgraph for GenAI applications (AI Agents, chatbots).
- Strong communication and presentation skills for various audiences.
- Ability to collaborate closely with business, engineering, and product teams.
- Experience in hiring data scientists and establishing team best practices is preferred.
Benefits
- Equity