Raise is the leading digital prepaid and retail payments platform where consumers can save money and earn rewards on every purchase. With over 450 national brands partnerships, Raise offers an opportunity for retailers to redefine their customer acquisition and retention strategy through direct-to-consumer relationships that empower consumers to maximize their spending.
Since 2013, we’ve saved millions of consumers over $150 million and have received $147 million in funding from investors including Accel, PayPal, Bessemer Venture Partners and New Enterprise Associates.
About the Position
Raise Data Scientists are a critical component of the cross-functional squads that make up the Raise technology organization. As a Data Scientist as Raise, you will be working in a collaborative environment on high-impact initiatives that support Raise’s product, sales, marketing, and leadership teams with insights gained from analyzing company data. You must have strong programming skills and a deep interest in understanding and applying statistical and machine learning methods to solve challenging real-world problems as part of a dynamic team.
Because we care deeply about building great products for everyone, we have spent a lot of focus on creating an environment that is inclusive, friendly, and empathetic. Therefore, the successful Data Scientist at Raise will not only excel technically, but also be people-focused, consistently striving to support the success, satisfaction, and empowerment of their fellow colleagues, business partners, and, ultimately, the Raise community.
- Execute quantitative analyses that translate into actionable insights to drive optimization and improvement of product development, marketing techniques, and business strategies
- Coordinate with different functional teams to develop and implement custom data models on BI tools
- Validate reports and dashboards that continually support executive decision-making and business strategies
- Apply data processing techniques (e.g., querying and wrangling data), statistical analyses, predictive modeling, and machine learning
Skills & Qualifications
- Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Physics, Machine Learning, or related discipline
- Experience using statistical computer languages (e.g., R, Python, SQL)
- Able to understand various data structures and common methods of data transformation
- Knowledge of basic and advanced statistical and predictive models (e.g., statistical distributions and tests, descriptive analysis, GLM/regression, customer LTV prediction, item-based and user-based filtering, pricing) and their proper usage
- Knowledge of machine learning techniques (e.g., clustering, random forests, Monte Carlo, SVM, network analysis, text mining) and their real-world advantages and limitations
- Strong written and verbal communication skills
- Familiarity with data visualization and dashboard creation tools, such as Tableau and Looker, is a plus
- Passionate about leveraging your coding skills to solve real-world, hard problems
- Natural curiosity and desire to learn, coupled with a drive to master new technologies and techniques
- Positive, people-oriented, and energetic
- Able to work independently and be self-motivated, highly organized, and be able to prioritize and manage multiple tasks
- Able to work in a rapidly changing and fast-paced environment
- Able to establish and maintain strong working relationships (i.e., collaborate with others) to achieve results
- Comprehensive benefits package including health, dental, vision, 401(K) plan, company paid short term and long-term disability and life insurance
- Flexible Paid Time Off Policy
- Raise Gives Back, paid time off for volunteering
- Pre-tax commuter program
- Paid maternity leave
- Paid parental leave
- Credits for employees
- Company provided snacks, coffee and soda
- Voluntary benefits like Pet Insurance and Identity Protection