Applied Scientist II, Core Analytics and Science

Key Skills

Java Programming, Design, Python Programming, SQL, Deep Learning, R Programming, SPARK Programming, Statistical modeling, Mixpanel, Data Analysis

Job Description

The Core Analytics & Science Team (CAS) is Uber's most extensive data science organisation, covering both of Uber's main lines of business as well as the underlying platform technologies that power those businesses. We are a vital part of Uber's cross-functional product development teams, helping to drive every stage of product development through data analytics, statistical, and algorithmic expertise.

The team at Bangalore, India, will host an entrepreneurial attitude that will focus on the rapid experimentation of ideas to expand the product portfolio for Uber. This team is regarded as one of the top-performing DS teams across Uber. This team is working to bring a customer-centric experience to our riders, at par with the Uber experience that they have come to expect. We are looking for a high-performing Applied Scientist to make significant contributions to our mission. A deep analytical passion for learning and the ability to execute on key business priorities is a must.

As an Applied Scientist for the team, you will play the significant role of helping define the product vision and deliver it from the ground up by working with a very fast-paced and passionate group of high-performing Data Scientists, Applied Scientists, Engineers, Designers, Product Managers, and Ops Managers. People with an entrepreneurial bent of mind, independent analytical thinking, rapid hypotheses building, testing hypotheses using experimentations, building machine learning/deep learning models, and apply causal inferences to aid the team make an informed decision and deliver high business impact.

What You'll Need

• Knowledge of underlying mathematical foundations of statistics, machine learning, economics, and analytics.
• Experience with exploratory data analysis, statistical analysis, hypotheses testing, machine learning, deep learning, and causal inferences.
• Strong experience and fluency in using Python, Spark or any other procedural programming and working efficiently at scale with large data sets.
• Experience in building and evaluating algorithms and optimising for performance in production.
• Experience with designing traditional and advanced experiments to test the right product outcomes.
• Experience with NLP is a plus but not required.
• Proven experience of 4+years in the relevant field.
• MS or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, Computer Science or other quantitative fields.

What You'll Do

• As an Applied Scientist, you will work closely with product management, engineering and operations teams to own applied science in driving Uber's product roadmap for Mobility Growth and New Verticals (e.g. High Capacity Vehicles, Micro Mobility, Rents) globally.
• Drive clarity and solve ambiguous, challenging business problems using data-driven approaches. Propose and own data analysis (including advanced modeling, coding, analytics, and experimentation) to drive business insight and facilitate decisions.
• Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, deep learning, causal inference, statistics, and optimisation, and work with engineering/product to deploy those algorithms and create impact in production.
• Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends
• Design product experiments and interpret the results to draw detailed and impactful conclusions and communicate with senior management and multi-functional teams
• Build and manage production-level algorithms that aid in ranking the right products to our riders, segmenting the riders to upsell the right product offerings, neural engines for contextual recommendations.
• Designing Travel Time Model, ETAs, Routes, Schedules, and Pricing for our new verticals such as HCV, Mimo and Rents.

Basic Qualifications

• PhD, MS or Bachelors degree in, Statistics, Economics, Machine Learning, Operations Research, Computer Science or other quantitative fields. (If M.S. degree, a minimum of 2+ years of industry experience required and if Bachelor's degree, a minimum of 4+ years of industry experience required)
• Knowledge of underlying mathematical foundations of statistics, machine learning, optimisation, economics, and analytics
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis, and testing, and model development
• Proficiency in languages and tools like Python, R, Spark, Hive, and SQL to work efficiently at scale with large data sets

Preferred Qualifications

• 4+ years of industry experience working as an applied scientist or similar
• Tech lead experience is a plus
• Experience solving ambiguous business problems at scale
• Experience with Causal inference techniques to evaluate the causal relationships with variables
• Experience building production-level machine learning and deep learning models
• Advanced expertise in experimental design and analysis (e.g., A/B and market-level experiments)
• Experience with productionizing algorithms for real-time systems