Data Scientist Ii, Fintech

2 weeks ago

Hyderabad Telangana, India Uber Full time

Work with tax operations, product, compliance, engineering, ops, accounting and other business stakeholders in mining and analyzing tax financial and entity-level data to extract key trends and insights.
- Investigate and resolve discrepancies in tax data, generate reports for external data sharing.
- Build effective visualizations to communicate data to key decision-makers. Be a trusted advisor to stakeholders cross-functionally.
- Build models to automate detection of anomalies/inconsistencies in tax data and resolve the same;
- Understand critical interdependencies across functions and divisions, and facilitate business decisions.
- Explore FinTech systems/data to proactively identify and initiate process improvements for cost savings and efficiencies.
- Communicate your findings to cross-functional peers and management.
- Get a deep understanding about the Tax systems and data flows involved; document and train internal personnel to institutionalize the learnings of the data science practice.
- Basic Qualifications
- M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitaxtive fields. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience as a Data Scientist or equivalent)
- Advanced SQL expertise
- Basic understanding of statistical methods
- Ability and experience in extracting insights from data, and summarizing learnings / takeaways to cross-functional stakeholders.
- Experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar)
- Preferred Qualifications
- Experience with either Python or R
- Experience working on analytics in accounting, finance areas
- Strong communication and organization skills
- Ability to multi-task while maintaining quality and detail
- Basic understanding of experimental design (such as A/B experiments) and statistical methods
- Demonstrated aptitude toward data storytelling and root cause analysis using data
- Ability to build models to detect anomalies and resolve financial imbalances
- Ability to understand critical interdependencies across functions and divisions, as well as the short and long-term trade-offs of business decisions.

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