Sr. Data Scientist
Baltimore, MD, US, 21230
Values & Innovation
At Under Armour, we are committed to empowering those who strive for more, and the company's values - Act Sustainably, Celebrate the Wins, Fight on Together, Love Athletes and Stand for Equality - serve as both a roadmap for our teams and the qualities expected of every teammate.
Our Values define and unite us, the beliefs that are the red thread that connects everyone at Under Armour. Our values are rallying cries, reminding us why we're here, and fueling everything we do.
Our pursuit of better begins with innovation and with our team's mission of being the best. With us, you get the freedom to go further - no matter your role. That means developing, delivering, and selling the state-of-the-art products and digital tools that make top performers even better.
If you are a current Under Armour teammate, apply to this position on the Internal Career Site Here.
Purpose of Role
We are looking for a Sr Data Scientist to join our Enterprise Data Management organization. As a member of the enterprise data science team, you will work on machine learning solutions supporting all of Under Armour’s business units across the globe. You will be challenged to identify creative solutions to real world problems by leveraging cutting edge machine learning and statistical techniques, while striving to maintain rigorous scientific and engineering standards. You will collaborate with other data scientists, engineers, and business decision makers to develop the next generation of data driven products and initiatives at Under Armour.
Your Impact
- Support global price optimization workflows by developing, maintaining, and expanding machine learning solutions supporting initial ticket price (ITP) optimization, promotional effectiveness, and product markdown optimization.
- Leverage AWS cloud computing solutions to develop and deploy models at scale, adhering to internal best practices in data science and MLOps.
- Propose novel statistical and machine learning methods to address key business challenge.
- Beome an expert in our internal price optimization modeling methodology -extracting and communicating insights and use cases to non-technical stakeholders and decision makers.
- Stay up-to-date with latest technology and modeling techniques
- Work collaboratively to drive improvements through the lifecycle of each product to ensure the technical implementation appropriately aligns with business goals.
Qualifications
- Bachelor’s degree, in Computer Science, Applied Mathematics or other quantitative disciplines, with 5+ years of relevant experience OR Master’s degree with typically 3+ of relevant experience OR 9+ years of relevant experience without a degree.
- Proficiency with SQL and Python.
- Practical work experience with one or more of the following: XGBoost, LightGBM, Prophet, supply chain optimization models, Bayesian statistics.
- Ability to apply data science to real-world problems, capable of breaking down complex problems into key components solvable by machine learning solutions.
- Knowledgable of limitations and best practices related to model specification, comparison, selection, and deployment.
- Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise
- Prior experience with AWS services (e.g., Sagemaker, S3, ECR) preferred.
- Prior experience working on an agile team preferred
- Prior experience leveraging version control (e.g., Git, SVN) in a team setting preferred
Workplace Location
- Location: Fully Remote
- Return to Work Designation: Fully Remote
- Travel: 5% of the year
- Licenses/Certifications: N/A
Relocation
- No relocation provided
Base Compensation
$127,496.00 - $175,307.00 USD
Most new hires fall within this range and have the opportunity to earn more over time. Initial placement within the salary range, however, is based on an individual's relevant knowledge, skills and experience for the position. UA is committed to helping our teammates succeed and advance in their careers. Base salary is only one component of our competitive Total Rewards package.
Benefits & Perks
- Paid "UA Give Back" Volunteer Days: Work alongside your team to support initiatives in your local community
- Under Armour Merchandise Discounts
- Competitive 401(k) plan matching
- Maternity and Parental Leave for eligible and FMLA-eligible teammates
- Health & fitness benefits, discounts and resources- We offer teammates across the country programs to promote physical activity and overall well-being
Our Commitment to Diversity
At Under Armour, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, color, religion or belief, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, family or paternal status and any other characteristic protected by applicable law. Under Armour believes that diversity and inclusion among our teammates is critical to our success as a global company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. Accommodation is available for applicants with disabilities upon request.
ApplyJob Profile
Fully remote
Benefits/PerksFlexible work environment Fully remote Health & fitness benefits Innovation Innovation-driven culture Maternity and parental leave Merchandise discounts Total Rewards package Volunteer days
Tasks- Collaborate with teams
- Communicate insights
- Develop machine learning solutions
- Support price optimization workflows
Agile AWS Bayesian Statistics Cloud Data Management Data Science Git Lightgbm Machine Learning MLOps Prophet Python SQL Statistical techniques Supply chain optimization SVN XGBoost
Experience5 years
EducationBachelor's degree Master's degree Quantitative Disciplines
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9