Senior Data Scientist II - AI for Analytics

Instacart Instacart · Consumer · Canada · Remote · Data Science

Instacart is seeking a Senior Data Scientist II to drive AI for Analytics initiatives. This role involves identifying product opportunities using data, deploying AI systems in production, and enhancing product features with intelligent functionality. The ideal candidate will have extensive experience in data science, Python, SQL, and building production ML models, with a focus on driving product strategy and collaborating cross-functionally.

What you'd actually do

  1. Product strategy: Using data to identify the most promising opportunity areas along with contributing data expertise to refine and develop new product ideas.
  2. AI expertise: You will be using and deploying a variety of AI systems in production settings.
  3. 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
  4. 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).
  5. Create the product roadmap

Skills

Required

  • 6+ years of work experience in a data science or related field
  • Deeply engaged with AI workflows
  • Expert in Python (pandas)
  • SQL
  • git
  • Jupyter notebooks
  • Strong statistical and analytical skills
  • Built a machine learning, statistical, or AI model that made its way into production

Nice to have

  • 8+ years of work experience in a data science or related field
  • 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
  • Significant causal experimentation experience
  • Built a complex machine learning or statistical model and deployed/supported it in production
  • 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

What the JD emphasized

  • 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

Other signals

  • increase the number of features launched by 2x by the end of 2026 by effectively using AI
  • developing systems to accelerate analyses completed by data experts and enable anyone to self-serve most analytics questions
  • driving AI for Analytics data science work
  • using and deploying a variety of AI systems in production settings
  • improving a product feature by adding intelligent functionality to the product that relies on data science methods including statistical and machine learning methods
  • Built a machine learning, statistical, or AI model that made its way into production