# Senior Machine Learning Engineer, Economist

**Company**: Instacart
**Location**: Canada - Remote (ON, AB, BC, or NS Only)
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: CAN$180,000-$190,000 CAD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/instacart/jobs/8157738?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_11fcda52-4dc

## Description

At Instacart, we're transforming the grocery industry by delivering an essential service that customers rely on to get their groceries and household goods. As a Senior Machine Learning Engineer, Economist, you will build state-of-the-art systems that blend rigorous economic thought with sophisticated machine learning algorithms to tackle some of the company's most challenging problems.

## Overview

As a machine learning engineer in the Economics team, you will have the opportunity to collaborate closely with partners across multiple functions to operate on a highly diverse set of problems, contributing both economic and engineering expertise in a fast-paced environment filled with exciting opportunities for technically-minded economists.

## Responsibilities

- Design, develop, and deploy machine learning solutions to tackle the many economic challenges in our complex marketplace.

- Collaborate closely with product managers, data scientists, and other engineers to deeply understand business needs and create impactful solutions.

- Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.

- Be an active member of the Economics team, sharing learnings, best practices, and research across domains while refining and advancing our algorithms.

## Requirements

- Graduate Degree (Masters or PhD) in Economics or a closely related field.

- A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one.

- Experience applying causal inference methodologies to both observational and experimental datasets.

- An understanding of machine learning algorithms and techniques.

- Strong programming skills (Python) and fluency in data manipulation (SQL, Pandas) and machine learning tools (e.g., scikit-learn, XGBoost).

- Excellent communication skills (both verbal and written).

- Self-motivation and a strong sense of ownership.

## Preferred Qualifications

- A PhD in Economics or a closely related field with a focus on data-intense problems.

- Intern experience in related roles.

- Experience with large language models and generative AI, both on the algorithm side as well as a day-to-day tool.

- Experience with uplift modeling, contextual bandits, and/or heterogeneous treatment effect estimation.

## Skills

### Required
- Python
- SQL
- Pandas
- scikit-learn
- XGBoost
- machine learning
- causal inference
- econometrics
- economics

### Nice to have
- large language models
- generative AI
- uplift modeling
- contextual bandits
- heterogeneous treatment effect estimation

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/instacart/jobs/8157738?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)