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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
We are looking for economists and machine learning engineers to join our fast-moving team. The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making.
There is tremendous opportunity in front of us, and joining now gives you a chance to grow your career and interests as we succeed.
ABOUT THE ROLE
The ideal candidate for this role will bring a combination of experience in both economics and machine learning. This might be a recent economics PhD graduate with relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications. We are also interested in candidates with industry experience in the creation, deployment, and maintenance of machine learning models at scale, especially if they have some background or experience in economics or an economics-adjacent field. More senior candidates are also welcome to apply.
ABOUT THE TEAM
The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference.
ABOUT THE JOB
- You will help design and build end-to-end machine learning solutions
- You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects
- You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains
- You will develop high impact solutions to support Instacart's ambitious growth plans
- You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments
- You will have the freedom to suggest and drive organization-wide initiatives
ABOUT YOU This section must have two lists: Minimum & Preferred
MINIMUM QUALIFICATIONS
- Graduate-level research experience on data-intense problems or 1+ years of industry experience in machine learning or economics-focused roles.
- A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one.
- Expertise in causal inference with observational and experimental data.
- Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
- An ability to identify and prioritize high-impact problems and deliver solutions that provide reasonable trade-offs between urgency and quality.
- Willing and able to travel internationally based on job requirements
- Self-motivation and a strong sense of ownership
PREFERRED QUALIFICATIONS
- PhD in Economics with focus on data-intense problems or 3-5 years of industry experience in machine learning or economics-focused roles.
- A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one.
- Expertise in causal inference with observational and experimental data.
- Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
- An ability to identify and prioritize high-impact problems and deliver solutions that provide reasonable trade-offs between urgency and quality.
- Willing and able to travel internationally based on job requirements
- Self-motivation and a strong sense of ownership
- Nice to have: Experience with training large-scale models and model deployment on cloud services (Docker, AWS/GCP/Azure).
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.
Instacart New York, New York, USA Office
Located in the historic Flatiron District, our NYC office sits just steps from the iconic Flatiron Building surrounded by shops and restaurants.
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