Sr Applied Data Scientist - Item Recommendations (applied ML, PyTorch, ML Ops)

Target

Hybrid

Quick summary

Work type
Hybrid
Location
Brooklyn Park, MN
Salary
$98,000–$176,000 / yr
Posted
2 days ago
Closes
Jul 24, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $174k
This role $137k
$83k most similar roles pay here $240k

This role pays less than 74% of similar roles. Most pay $133,750–$214,029 — the shaded band above. At the midpoint, this role pays about $137k versus about $174k 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 $118,000–$211,000 across 49 roles with salary data.

Most-posted roles

View all roles at Target

At a glance

TL;DR · Sr Applied Data Scientist - Item Recommendations (applied ML, PyTorch, ML Ops)

As a Senior Data Scientist on Target’s Recommendations team, you will collaborate with data scientists, machine learning engineers, and product managers to develop AI-driven recommendation products. Your daily tasks include performing data exploration, implementing algorithmic solutions using deep learning frameworks like PyTorch or JAX, and analyzing model performance through offline analysis and online experimentation. You will also contribute to maintaining a well-documented codebase and presenting technical findings to both technical and non-technical stakeholders. The role requires strong skills in Python, SQL, and large-scale data processing platforms such as Spark, along with expertise in optimization, statistics, and experimental design. This position involves addressing complex business challenges by translating them into scalable data science solutions within a fast-paced, collaborative global environment.

What you'll do

  • Conduct data exploration and analysis using deep learning frameworks like PyTorch.
  • Implement algorithmic solutions for recommendation systems based on technical specifications.
  • Evaluate machine learning models through offline analysis and online experimentation.
  • Document and present complex technical concepts to both technical and non-technical peers.
  • Translate business problems into scalable data science solutions, aligning with strategic goals.
  • Maintain a well-tested codebase and participate in code reviews following best practices.

What we're looking for

  • MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research or equivalent experience.
  • 3+ years developing machine learning models using deep learning frameworks like PyTorch or JAX.
  • Experience building recommendation and personalization systems at scale.
  • Strong programming skills in Python and SQL with optimization expertise.
  • Proficiency in evaluating models through offline analysis on large datasets and online experimentation.
  • Knowledge of large-scale data processing platforms such as Spark and experience with generative AI tools.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical audiences.

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