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 a 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).
About the role
As a Data Scientist, you will get involved on projects that encompass the foundational principles of data science, such as Machine Learning, Causal Inference, and Experimentation.
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 high complexity and impact, 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 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: Design and run experiments in the uber marketplace 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).
You will guide Team Members on estimating and executing technical tasks, mentor interns and coach junior talents on best practices.
What you'll do
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 a 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).
About the role
As a Data Scientist, you will get involved on projects that encompass the foundational principles of data science, such as Machine Learning, Causal Inference, and Experimentation.
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 high complexity and impact, 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 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: Design and run experiments in the uber marketplace 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).
You will guide Team Members on estimating and executing technical tasks, mentor interns and coach junior talents on best practices.
What you'll do
- Design, lead & execute large scale projects, proactively
- Engineer features, deploy models and improve them as needed
- 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
- Interact with multiple Stakeholders across globally, present your results in a concise manner
- Guide Team on execution of technical tasks, backlog break-down and estimate
- Coach Team Members on best practices, mentor junior talents or interns
- Assess Candidates on their technical competencies during recruitments
- Strong knowledge in SQL, Python (Pandas Library, basics of OOP)
- Good experience in common ML frameworks, tools & libraries (Scikit-Learn, Scipy, PyTorch, Tensorflow)
- Proficient knowledge of ML methods (Neural Networks, Naive Bayes, SVM, Decision Forests, etc.)
- 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
- Ability to:
- engineer features, deploy models and improve them as needed
- analyze complex datasets, visualize and report your findings, storytell (knowledge in data visualization softwares)
- Strong Stakeholder Management and communication skills, with the ability to:
- Work with many business Stakeholders and tailor solutions to their needs
- Explain complex technical details to non-technical business audience (excellent written and spoken English)
- Proven track records as Junior Data Scientist or equivalent with experience in Scrum, Google Sheets, Data Studio, preparation of technical documentation
- Motivation to learn all along the way and improve continuously
Report job
