Data Scientist III at UBER FREIGHT US LLC

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

11 May, 26

Salary

0.0

Posted On

10 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Statistical Modeling, Machine Learning, SQL, Python, Data Analysis, Collaboration, Data Wrangling, Attribution Frameworks, Experiment Design, Statistical Methods, Operational Excellence, Logistics, AI Implementations, Data-Driven Insights, Cross-Functional Teams, Process Improvements

Industry

Logistics;Transportation;Supply Chain and Storage

Description

Schedule: FT Job Type: Hybrid Salary Type: Salary Req #: 2017 About the Role We are seeking an exceptionally passionate person to join our Data Science team to architect the future of Uber Freight Analytics. In this role, you will go beyond standard reporting to drive an analytics roadmap that unlocks Operational Excellence (OpEx) across the business. You will deliver advanced descriptive and predictive solutions to Operations, Finance, and Logistics leadership, leveraging statistical modeling and machine learning to optimize logistics workflows, identify cost-saving opportunities, and provide the groundwork for AI-driven automation. You will collaborate across functions to solve complex problems, create massive operational efficiencies, and ensure every initiative is backed by a rigorous, data-driven impact attribution. What the Candidate Will Do Perform deep-dive exploratory and statistical analysis to uncover hidden inefficiencies in global logistics networks and deploy ML models that drive automated decision-making. Apply advanced statistical analysis to identify OpEx opportunities and provide the data-driven insights necessary to architect and facilitate large-scale AI implementations. Develop robust attribution frameworks to quantify the financial and operational impact of process improvements, ensuring alignment with core company priorities and cost-reduction targets. Collaborate with cross-functional teams such as product, engineering, and operations to drive system development end-to-end from conceptualization to productization Wrangle and synthesize fragmented data from multiple providers and internal systems to create a 'single source of truth' for operational performance Basic Qualifications Bachelor’s degree in Statistics, Mathematics, Computer Science, or related field 3 years of related experience Experience with SQL, Python Preferred Qualifications Masters with 3 years of experience or Bachelors with 5 years of relevant experience Experience with orchestration tools (e.g., Airflow) Experience with Spark Advanced knowledge of experiment design and statistical methods Strong presentation skills Experience working in a supply chain / logistics domain About Uber Freight Uber Freight is a market-leading enterprise technology company powering intelligent logistics. With a suite of end-to-end logistics applications, managed services and an expansive carrier network, Uber Freight advances supply chains and moves the world’s goods. Today, the company manages nearly $20B of freight and one of the largest networks of carriers. It is backed by best-in-class investors and provides services for 1 in 3 Fortune 500 companies, including Del Monte Foods, Nestle, Anheuser-Busch InBev, and more. For more, visit www.uberfreight.com. Candidate Privacy Notice Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice. EEOC Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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Responsibilities

The candidate will perform deep-dive exploratory and statistical analysis to uncover inefficiencies in logistics networks and deploy machine learning models for automated decision-making. They will collaborate with cross-functional teams to drive system development from conceptualization to productization.