Office Manager & POps Coordinator
You will support the SIMA Angaza Distributor Finance Fund (DFF), which is unlocking capital for small & med. distributors across Africa. You will be a vital member of our Business Intelligence team reporting to the Dir. of Analytics and providing mentoring & advice to more junior team members. Finally, you will be responsible for surfacing insights into drivers of distributor success & supporting Angaza’s Product team in better serving distributors. Angaza is building out its data science capabilities around a deep commitment to our core values, proven development practices, & a philosophy of continuous professional development.
- Distributor Finance Fund (DFF): Conduct statistical analyses to drive optimal decision-making across DFF’s risk management lifecycle (sourcing, underwriting, portfolio mgmt)Develop statistical model(s) using end-client transaction data to assess credit risk of PAYG distribution businesses
- Decision Science: Create forecasting tools for customer performance and customer segmentation by correlating leading indicators with their success
- Product: Collaborate with our engineering team to develop new data science product features
- Thought leadership: Set the direction of our data science practice, mentor other data team members, and effectively communicate methodology and findings with internal and external stakeholders
Competencies and Expertise:
- Statistics: Well-versed in advanced statistical methods (regression, confidence intervals, classification, linear algebra, Monte Carlo simulation, etc.), with demonstrated professional experience leading the design and deployment of statistical models
- Programming Skills: Experience deploying data science tools in your preferred programming language. (Our BI and Engineering teams currently operate mostly in Python.)
- Credit risk analysis: Experienced in evaluating credit risk (emerging market consumer lending; small/ medium business lending; or PAYG sector knowledge a plus)
- Resourcefulness: Comfortable working to solve ambiguous problems in new subject areas with a flexible approach
- Cross-functional collaboration: Able to work effectively with others from a range of functions and backgrounds (e.g., customer credit, engineering, and product teams, as well as DFF investors)
- Thrive in a cooperative, dynamic environment
- Are passionate about presenting data that communicates complex information in a straightforward way
- Have strong quantitative, problem-solving, and project management skills
- Demonstrate excellent written and verbal communication skills
- Pride yourself on attention to detail
- Exemplify Angaza’s key values: maximizing impact, empathetic, courageous, trustworthy, curious, and collaborative
- The strongest candidates will have approximately ten years overall advanced educational and work experience and at least three years experience in one or more of the following categories:
- Demonstrated experience in leading design and deployment of data science models / tools
- Assessing credit risk (consumer and/or small/medium business, direct experience in emerging markets preferred) using statistical methods
- Supporting executive decision-making through descriptive and statistical analysis at an early-stage organization
San Francisco Office Preferred, must have significant time zone overlap with our SF-based team members. Note that Angaza’s customers largely operate in Africa and you may need to be available for phone calls on their schedules.
Angaza is a for-profit company with offices in San Francisco and Nairobi. Employees receive salary, an equity stake in Angaza, and benefits that include:
- Competitive health benefits including medical, dental, vision, life, disability, HSA, & FSA
- 401(k) with company match
- Fully paid parental leave
- Flexible scheduling and time off policies
- Knowledge that you’re making a positive impact on the world every day you come to work!
Our Commitment to DEI:
At Angaza, we evaluate all candidates on the basis of their ability to meet stated job requirements. We do not discriminate against candidates on the basis of sex, gender, marital status, religion, nationality, or other personal characteristics. In keeping with our commitment to supporting a safe and inclusive workplace, we strongly encourage candidates from traditionally underrepresented backgrounds to apply.