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Staff Data Scientist 775 views

At Uber, they ignite opportunity by setting the world in motion. They take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.

They welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with them, and let’s move the world forward, together.

About The Role

The quantitative research team within Strategic Finance is looking for a Staff Data Scientist who will help raise the bar for technical rigor across their combined Finance Data Science and Analytics organization. You will be using your broad array of technical skills and knowledge to drive key financial decisions. This is a unique opportunity to have a direct impact on building an efficient transportation system on a global scale. You will be part of the leadership team for a ~40 person organization and help set the vision for the team going forward.

About The Team

Uber’s Finance Data Science organization leverages state-of-the-art algorithms, methodologies, tools, and frameworks to achieve a strong global operating cadence, efficient annual financial planning, and accurate monthly forecasting. They help set the business strategy, allocate capital, and analyze the impact of investments across all lines of businesses including Rides, Eats, Freight, and New Mobility. The team builds and refines cutting-edge valuation models to assess long-term customer profitability using Machine Learning/Deep Learning algorithms. They play an influential role in improving unit economics and building a profitable/sustainable business at Uber.

What You’ll Do

  • Lead cross-functional teams to research, build & constantly improve a suite of machine learning, forecasting, and optimization models/frameworks that help Uber plan and invest intelligently with respect to their financial goals
  • Evangelize Data Science frameworks with a broad group of stakeholders including Strategic Finance, Financial Technology, Engineering, Product, Marketing, and other global organizations
  • Dive deep into their most complex Data Science problems and leverage Uber’s complex data ecosystem to develop disruptive but actionable business insights
  • Advise senior management to strengthen critical investment decisions and to revolutionize forecasting, planning, valuation, profitability, revenue management platforms
  • Act as a technical mentor to their top talent, develop internal training programs, and create global talent pipelines
  • Elevate their brand by representing their work at internal/external Data Science conferences, seminars, and meet-ups

What You’ll Need

  • Excellent educational background in Machine Learning, Statistics, Mathematics, Economics, Operations Research, or a related field. Masters or Ph.D. degree preferred.
  • At least 8+ years of industry experience in Data Science with significant personal experience as a technical contributor.
  • Recognition as a global leader in at least two Data Science specialties (i.e. Time-series Forecasting, Causal Inference, Statistics, Deep Learning, NLP, Recommender Systems, etc.)
  • Some experience as a technical mentor/coach. You will not have formal management responsibilities but will be expected to act as a technical mentor to several Senior Data Scientists.
  • Entrepreneurial mindset. Everywhere you go, you can’t help but mobilize people, create things, solve problems, roll up your sleeves, collaborate, go above and beyond. You are an insatiable doer and motivator of others.
  • Excellent execution and organization. This team will be working with Finance and Product leaders at the forefront of the development cycle. To excel in this role, you should be comfortable executing with little oversight and be able to adapt to problems quickly.
  • Demonstrable expertise in coding (Python, Spark, and R preferred) and programming concepts
  • A strong communicator who can partner with others to set a vision and then collaborate to deliver impactful results that are well explained

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