Data Scientist - Delivery (Senior/Staff)

Key Skills

A/B Testing, Data science techniques, Git, Jupyter Notebook, Machine learning techniques, Pandas, Python Programming, PyTorch, Scikit-learn, Snowflake, SQL

Job Description

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

OVERVIEW

Instacart’s core product is grocery delivery. Grocery delivery relies on shoppers picking, paying for, and delivering grocery orders to customers. Fulfillment Tech builds all the technology that shoppers use to pick, pay for, and deliver orders to customers. The Delivery team focuses on ensuring every order is delivered on time and accurately to customers. 

ABOUT THE JOB

You would be responsible for leading the Delivery 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
• Impact sizing: Providing an estimated impact of implementing a new feature
• Impact measurement: Running an experiment to determine the actual impact of newly launched product features
• 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 two most important responsibility areas of this role are product strategy and intelligent systems.

Product strategy: The best products are built with diversity of thought. Data scientists uniquely understand the available data, the business domain, and the advanced methods that can be applied to the data to drive the desired business outcome. There are two primary methods data scientists would add value in product strategy:

• Clearly represent the right problem to solve to the team by providing a deep, data-driven understanding of the problem area with the team as well as identifying the most promising opportunity areas within the problem space
• Contribute product ideas that leverage intelligent systems to solve the problems identified while collaborating closely with product, research, design, and engineering teams on the overall solution.

Intelligent systems: Intelligent systems make products smarter by combining deep domain expertise with advanced statistical or ML approaches. Data scientists are uniquely positioned to combine their understanding of the domain and advanced statistical methods to rapidly iterate on different approaches to building an intelligent system to solve an ambiguous problem. They would invest time in creating the initial version of the intelligent systems while partnering with MLEs and SWEs to maximize the impact, scalability, and maintainability of the system.

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

1. 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).
2. Bring new ideas to the team that get incorporated into the product roadmap
3. Ruthlessly prioritize among requests from multiple competing stakeholders

ABOUT YOU

Minimum Qualifications

4+ years of work experience in a data science or related field, and led a team to adopt at least one new metric with which to measure the performance of the team. Also: 

• Ran an A/B test at a company
• Built a machine learning or statistical model that made its way into production even if the code you wrote was completely rewritten before being deployed
• Experience with Python (pandas), SQL, git, and Jupyter notebooks

Preferred Qualifications

6+ years of work experience in a data science or related field, and 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. Also:

• Significant causal experimentation experience in environments with small sample sizes
• 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

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For US based candidates, the base pay ranges for a successful candidate are listed below.

CA, NY, CT, NJ

$185,000—$230,000 USD

WA

$177,000—$221,000 USD

OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI

$170,000—$212,000 USD

All other states

$153,000—$191,000 USD