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Home›Jobs›Uber›Data Analytics Specialist III - Junior Data Scientist
Uber

About Uber

Reimagining transportation for a better world

🏢 Tech👥 1001+ employees📅 Founded 2009📍 Mission Bay, San Francisco, CA💰 $15.8b⭐ 3.9
B2CTravelMarketplaceTransportRidesharingDelivery

Key Highlights

  • Public company (NYSE: UBER) since May 2019
  • Completed over 1.5 billion trips globally
  • Generated $4.8B in revenue from Uber Eats in 2020
  • Raised $15.8 billion in funding

Uber Technologies, Inc. (NYSE: UBER) is a leading ride-hailing platform headquartered in Mission Bay, San Francisco, CA. Founded in 2009, Uber has transformed transportation services, completing over 1.5 billion trips globally. The company went public in May 2019 and has raised $15.8 billion in fund...

🎁 Benefits

Uber provides comprehensive healthcare, a robust employee stock purchase plan, generous paid vacation, and a four-week sabbatical after five years of ...

🌟 Culture

Uber fosters a culture of innovation and adaptability, continuously expanding its services beyond traditional ride-hailing. The company emphasizes wor...

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Uber

Data Analytics Specialist III - Junior Data Scientist

Uber • Krakow, POL

Posted 1 month ago🏛️ On-SiteJuniorData scientist📍 Krakow
Apply Now →

Skills & Technologies

Machine learningStatistical modelingCausal inferenceData analyticsData sciencePython

Job Description

**Junior Data Scientist** Uber is looking for a Junior Data Scientist to expand its Team in Krakow. The Krakow Center of Excellence is taking a new highway to become a major Technology Hub in Central & Eastern Europe, focusing on Data Science, Data Analytics & Automation. **About the role** As a Junior Data Scientist, you will get involved on projects that encompass the foundational principles of data science, such as Machine Learning, Experimentation, Statistical Modeling and Causal Inference. Most of your actions will hinge on these core and essential activities: aligning on business objectives, formulating problem statements, collecting, cleaning and structuring data, conducting analytical explorations, applying techniques for inferential and predictive modeling and effectively communicating outcomes. You will work on projects of varying sizes and time horizons, aligning your prioritizations with the Operations Coordinator. You will translate business questions into testable hypotheses and rigorous experimental designs, or into mathematical models and ML algorithms. You will deliver your work iteratively and incrementally, ensuring i) your code follows the best practices in terms of quality, reusability, optimization, ii) your analyses are robust, valid, reliable, scalable and impactful, iii) your deliverables are properly maintained and adapted to evolving requirements. You will investigate opportunities in various topics, such as: Market Expansion with randomized controlled trials (RCTs) or ML models for product launch; Market Health models or DnD models for policy evaluation; Audits with regression discontinuity design (RDD) or reinforcement control learning for auditing threshold; Document Processing with natural language processing (NLP) or optical character recognition (OCR) for document classification. **About the Team** Backing Uber’s creativity with operational efficiency. This is the Team’s mission statement. On request of Local, Central, Regional & Global Ops, the Team centralizes work, in Krakow CoE, around: - Business Processes (design, execution, enhancement, optimization) - Analytics & Automation (query, deepdive, self-operating dash., process automation) - Data Science (modeling, causal inference, experimentation, machine learning) This experience gained as Junior Data Scientist may also, going forward, open doors to plenty of new opportunities across the world, via the Uber Mobility Program. We’re offering a hybrid model of working (60% based out of our Krakow office, 40% work from home). **What you’ll do** - Formulate business questions into testable hypotheses and rigorous experimental designs - Collect and clean data, analyze experiments, infer causality and estimate effects - Use Statistical Modeling and ML to find patterns and make predictions from large datasets - Engineer features, deploy models and improve them as needed - Visualize and report your findings to Stakeholders, adapting your communication to a variety of audiences - Communicate findings to Stakeholders, adapting your communication to a variety of audiences **What you'll need** - Knowledge of causal inference, experimentation and econometrics statistics methods for analytical problems - Ability to design, conduct and analyze experiments to infer causality and estimate effects - Understanding of statistical modeling and ML to find patterns and make predictions from large datasets - Skilled in SQL and Python (Pandas Library, basics of OOP and API endpoints) - Hands-on experience in common ML frameworks, tools & libraries (scikit-learn, scipy) - Knowledge of ML methods (neural networks, naive Bayes, SVM, decision forests, etc.) - Ability to engineer features, deploy models and improve them as needed - Ability to visualize and report your findings to Stakeholders, adapting your communication to a variety of audiences - Motivation to learn all along the way and improve continuously Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let’s move it forward, together. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. \*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to [accommodations@uber.com](mailto:accommodations@uber.com).

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