Lead Applied Data Scientist - Digital Item RecSys (applied ML, deep learning)

Target

Remote Hybrid

Quick summary

Work type
Remote
Location
Remote
Salary
$132,000–$286,000 / yr
Posted
9 days ago
Closes
Jul 10, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $171k
This role $209k
$108k most similar roles pay here $305k

This role pays more than 65% of similar roles. Most pay $126,800–$214,850 — the shaded band above. At the midpoint, this role pays about $209k versus about $171k for comparable roles.

Based on 240 similar postings.

Employer

About Target

Target Corporation is a large-format general merchandise and grocery retailer offering a wide assortment of everyday essentials, apparel, home goods, and electronics through stores and online. Industry: General Merchandise Retail

Target currently has 49 open roles on FindRole.

Listed pay typically runs $115,000–$211,000 across 49 roles with salary data.

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View all roles at Target

At a glance

TL;DR · Lead Applied Data Scientist - Digital Item RecSys (applied ML, deep learning)

As a Lead Data Scientist at Target’s Digital Item Recommendations team, you will provide technical leadership for machine learning systems that enhance guest experiences through recommendation, retrieval, ranking, and personalization solutions. You will work closely with data scientists, engineers, product managers, and business stakeholders to identify opportunities for improvement and develop scalable algorithmic solutions that drive measurable impact. Your responsibilities include designing, developing, evaluating, and deploying machine learning models at massive scale using Python, SQL, PyTorch, or JAX, while also leveraging large-scale data processing platforms like Spark. You will mentor other scientists, establish best practices, and contribute to the growth of Target’s data science community by influencing decisions across product, engineering, and data science teams.

What you'll do

  • Lead the design and deployment of machine learning models for digital recommendations at scale.
  • Identify opportunities to enhance guest experiences through advanced recommendation solutions.
  • Translate complex business challenges into scalable algorithmic solutions driving measurable impact.
  • Mentor data scientists, establish best practices, and contribute to the growth of Target's data science community.
  • Drive projects from initial problem definition to production deployment and measurement.
  • Influence technical direction by shaping recommendation capabilities and collaborating with cross-functional teams.

What we're looking for

  • MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research or relevant industry experience.
  • Over 5 years of experience leading the development, evaluation, and deployment of machine learning solutions.
  • Proven expertise in building and scaling recommendation, personalization, ranking, retrieval, or search systems.
  • Strong programming skills in Python, SQL, and deep learning frameworks like PyTorch or JAX.
  • Experience with large-scale data processing platforms such as Spark.
  • Deep understanding of machine learning, deep learning, optimization, statistics, probability, and experimental design.
  • Ability to translate ambiguous business challenges into scalable algorithmic solutions.

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