Blend makes the process of getting a loan simpler, faster, and safer. With its digital lending platform, Blend helps financial institutions including Wells Fargo and U.S. Bank increase productivity and deliver exceptional customer experiences. The company processes nearly $2 billion in loans daily, helping millions of consumers gain access to the capital they need to lead better lives.
Blend is hiring a Product Analyst in San Francisco to help drive our Product Analytics efforts. You will partner closely with leaders across the organization, working together to understand the how and why of people, team and company challenges, workflows and culture. The team is responsible for delivering data and insights that drive decision making, execution and investments for our product initiatives.
You will work cross-functionally with product, design, engineering, and our customer-facing teams enabling them with data and narratives about the customer journey. You’ll also work closely with other data teams, such as data engineering and business operations, to ensure we are creating a strong data culture at Blend that enables our cross-functional partners to be more data-informed.
How you'll contribute:
- Partner closely with Product, Design, Customer Success, and Business Operations to drive impact through the product lifecycle. Develop objectives and metrics, ensure priorities are data-driven, and balance short-term and long-term goals
- Develop deep analytical insights to inform and influence product roadmaps and business decisions and help improve the consumer experience
- Work closely with Data Engineering to author and develop core data sets that empower analyses
- Deeply understand the business and proactively spot risks and opportunities
Who you are:
- 4+ years in the Analytics space
- Extensive relative experience in a high-performing Analytics team
- A proven track record of using analysis to drive key decisions and influence change
- Strong storyteller and ability to communicate effectively with managers and executives
- Demonstrated ability to define metrics for product areas, understand the right questions to ask and push back on stakeholders in the face of ambiguous, complex problems, and work with diverse teams with different goals
Nice to Haves:
- Understanding of fundamental probability and statistical concepts, such as hypothesis testing and regression
- Interest or experience in machine learning techniques(such as clustering, decision tree, and segmentation) is helpful, but not required
- Familiarity with a scientific computing language, such as Python
- B2B SaaS experience
Benefits and Perks:
- Meaningful equity and a 401(k) plan
- Comprehensive health benefits
- Sponsored gym memberships, ClassPass credits, or wellness stipend.
- Lunch, dinner, snacks, and Pizza Fridays
- On-site meditation, yoga, and massages
- Flexible work schedule, with open vacation policy
- 4 months of paid parental or personal leave
- Convenient location, with parking programs, and flexible commuter options