Sr Data Scientist - Merchandise Scaling (Applied ML, Python, ML Ops)) at Target

Brooklyn Park, Minnesota, United States

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$95,000 – $171,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

RetailIndustries

Requirements

PhD/MS in Applied Mathematics, Statistics, Operations Research, Industrial Engineering, Physics, Computer Science or equivalent work experience
3+ years of experience cleaning, transforming and analyzing large datasets for insights leading to business improvements - preferably in retail data
Experience developing, testing and maintaining large codebases in a collaborative environment while meeting industry best practices - including implementing and working with CI/CD pipelines (i.e. Docker, Kubernetes, etc.)
Demonstrated knowledge of mathematical and statistical concepts, data structures, algorithm design, data analysis, optimization, simulations and visualizations applied to business problems at scale
Good working knowledge of Python for Machine Learning, including supervised and unsupervised methods and their applications
Extensive experience with ML Ops, deploying solutions with large-scale impact
Self-driven and results-oriented, with the ability to meet tight timelines
Strong team player with the ability to collaborate across geographies/time zones
Excellent written and verbal communication skills
Ability to operate in a Hybrid/Flex for Your Day work arrangement, including onsite at Target HQ MN location

Responsibilities

Collaborate with Product, Tech, and business partners to solve retail challenges at scale for the merchandising organization
Design, develop, deploy, and maintain data science models and tools
Work closely with data scientists, engineers, and business partners to continuously learn and address evolving business needs
Collaborate with product and engineering partners on peer teams to build and productionize enterprise merchandising solutions
Develop and manage state-of-the-art predictive algorithms that use data at scale to automate and optimize decisions
Perform modeling and data science, software/product development of highly performant code for Model Performance
Apply retail domain knowledge to elevate Target’s culture

Skills

Python

Machine Learning

MLOps

Data Science

Predictive Modeling

Software Development

Model Performance

Target

Retailer offering diverse consumer goods

About Target

Target Corporation is a retail company that offers a wide range of products, including clothing, electronics, home goods, and groceries, through nearly 2,000 stores and an online platform. Its "Design For All" philosophy allows it to provide high-quality, affordable products that cater to diverse customer needs. Target differentiates itself from competitors with its owned brands and the Target Circle loyalty program, which enhances customer engagement. The company's goal is to support sustainability and community initiatives by giving back 5% of its profits to local communities.

Minneapolis, MinnesotaHeadquarters

2005Year Founded

N/ACompany Stage

Consumer GoodsIndustries

10,001+Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

Paid Sick Leave

Paid Holidays

Paid Vacation

401(k) Retirement Plan

Employee Discounts

Risks

Increased competition from online-only retailers like Amazon threatens Target's market share.

Rising labor costs due to new minimum wage laws could impact profit margins.

Supply chain vulnerabilities from geopolitical tensions may affect inventory and pricing strategies.

Differentiation

Target's 'Design For All' philosophy offers unique, high-quality products at affordable prices.

The Target Circle loyalty program enhances customer engagement and shopping experience.

Target's commitment to sustainability and community support sets it apart from competitors.

Upsides

Experiential retail and 'retailtainment' strategies can boost customer engagement and foot traffic.

Augmented reality integration offers immersive shopping experiences showcasing Target's unique designs.

Omnichannel retail strategies enhance customer experience by integrating online and offline shopping.

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