As a Senior Data Scientist, you will deliver analysis and communicate business metrics around customer engagement, financial ...
As a Senior Data Scientist, you will deliver analysis and communicate business metrics around customer engagement, financial product usage, fraud analysis, marketing analysis, etc. You know how to ask the right questions and are passionate about using data to support and drive informed business decisions. You'll guide our internal teams to use data to improve the product and achieve KPIs.
- Partner with Product, Marketing, Business Development, UX, Ventures, and Engineering teams to solve problems by providing data solutions
- Conduct trader behavior research, market data analysis, benchmark analysis, product analysis and blockchain data analysis to spot trend and identify opportunities for the business
- Build/maintain reports, dashboards, and metrics to support data informed decision making
Use analytical rigor and statistical methods, machine learning, programming, data modeling, simulation and advanced mathematics to analyze large amounts of data, recognizing patterns, identifying opportunities, posing business questions and making valuable discoveries
- Documents projects including business objectives, data gathering and processes, leading approaches, final algorithm, detailed set of results and analytical metrics
- Interprets and communicates insights and findings
- Collaborate with data engineers to identify data preparation/cleansing/ETL pipelines needs
- Provide mentorship and guidelines to junior team members
- 3+ years of working experience in analytics, Quant, data mining, and/or predictive modeling.
- 1+ years of experience in Financial services.
- Exceptional problem solving skills: demonstrated ability to understand business, challenges, structure complex problems and deliver solutions.
- Comfortable interacting with business peers to understand and identify use cases. Be able to articulate solutions & present them to business.
- Excellent communication and storytelling skills.
- Highly proficient in accessing data warehouses (SQL, AWS, proprietary equivalents).
- Familiarity with Python.
- Understanding of statistics (e.g., hypothesis testing, regression).
- Experience using common visualization tools (Tableau, Looker would be a plus).
- Degree in quantitative or computational field.