[Hiring] Senior Data Scientist II - AI for Analytics @Instacart

Role Description

Instacart will increase the number of features launched by 2x by the end of 2026 by effectively using AI. A primary driver of knowing which features to launch includes analytical work traditionally performed by data scientists in collaboration with a product team. We are developing systems to accelerate analyses completed by data experts and enable anyone to self-serve most analytics questions.

You would be responsible for driving AI for Analytics data science work which includes:

• Product strategy: Using data to identify the most promising opportunity areas along with contributing data expertise to refine and develop new product ideas.
• AI expertise: You will be using and deploying a variety of AI systems in production settings.
• Intelligent systems: Improving a product feature by adding intelligent functionality to the product that relies on data science methods including statistical and machine learning methods.

The role requires strong XFN collaboration where an ideal candidate can:

• Drive critical efforts to completion with little oversight, while occasionally jumping into roles adjacent to data science (i.e. data engineering, machine learning engineer, etc).
• Create the product roadmap.
• Ruthlessly prioritize among requests from multiple competing stakeholders.
• Act as a senior cross-functional leader of the team, aligning the team on principles, processes and goals.

Qualifications

• 6+ years of work experience in a data science or related field.
• Have deeply engaged with AI workflows.
• Expert in Python (pandas), SQL, git, and Jupyter notebooks.
• Strong statistical and analytical skills.
• Built a machine learning, statistical, or AI model that made its way into production even if the code you wrote was completely rewritten before being deployed.

Requirements

• 8+ years of work experience in a data science or related field (preferred).
• Led a cross-functional team to design a system of metrics that connected the business strategy to a set of core metrics and assigned ownership of those metrics to the team (preferred).
• Significant causal experimentation experience (preferred).
• Built a complex machine learning or statistical model and deployed/supported it in production (preferred).
• Experience with Python (pandas; scikit-learn, statsmodels, or PyTorch; a visualization library that is not matplotlib; a web framework such as flask), SQL (Snowflake), git, Jupyter notebooks (preferred).

Benefits

• Highly market-competitive compensation and benefits.
• Remote work flexibility.
• New hire equity grant and annual refresh grants.