Kiva (www.kiva.org) is a mission-driven technology non-profit. We run a global marketplace platform for crowd-funded micro-loans to serve the financially excluded in sectors such as education, water, clean energy, and refugee resettlement. Kiva combines the culture and approach of an internet start-up with a mission to alleviate poverty. We aim to drive social impact and enable opportunity while providing a borrower-to-lender connection: “Loans that change lives."​

In just 15 years, Kiva has raised nearly $1.5 billion in loan capital for more than 2 million borrowers in 84 countries. Kiva’s lenders fund over $1 million in loans every 3 days.

Headquartered in San Francisco, Kiva's team has 100+ employees and 450+ volunteers worldwide.

Role Overview

We are looking for a Sr. Product Data Analyst to join our expanding Data Analytics team. You’ll be joining a lean data-obsessed analytics team supporting stakeholders who are constantly on the hunt for impactful insights. This role will be responsible for delivering customer-focused data insights that inform the product roadmap and broader Kiva strategy, shedding light on key drivers of performance and growth, and developing Kiva’s product analytics roadmap. You will work closely with the product team to lead strategic efforts, define and measure success, and empower the team to achieve inspiringly ambitious impact goals. The role is fully remote (within the US).

Who We’re Looking For

We’re looking for someone who is passionate about the Kiva mission and has a track record of developing actionable product data insights, driving data self-service, and providing analytics thought leadership. You live and breathe data, are passionate about social good, and thrive in an environment where you get to dabble in both. You are ever-curious, comfortable in ambiguity, and not afraid to fail in the name of learning. You work well independently, and even better when put in a room with like-minded as well as diverse teammates.

At this time, we can only consider applicants with authorization to work in the United States; unfortunately we cannot provide visa sponsorship.

Key Responsibilities Include

• Collaborate with our product team to drive impactful user experience, acquisition, engagement, and retention initiatives using data.
• Develop a deep understanding of Kiva lenders by sifting through rich user behavior datasets, deriving and communicating insights on lender engagement and delight through the user journey.
• Use your statistical prowess to identify opportunities to engage
• Develop a robust product analytics framework by defining metrics, designing scalable product-specific data models, building critical company dashboards, and developing a core shared knowledge base.
• Perform ongoing trend analysis and shareouts to inform day-to-day decisions.
• Design, run, and analyze experiments to efficiently arrive at scalable insights that drive lender engagement and satisfaction.
• Be a strong voice in optimizing our analytics workflow and partner with data engineering in building scalable data solutions.
• Provide leadership on a range of analytics work occurring across the company, including mentoring data users in support of self-service (we use Looker, but experience in any BI tool will help).

Preferred Qualifications

• 5+ years experience in product analytics, data analytics, business analytics, data science, economics, statistics or related field.
• Consistent record of conducting proactive data analysis, distilling actionable takeaways, telling a story with data, making recommendations, and driving informed decision-making.
• Deep expertise in user-focused product analytics concepts such as user experience, user journeys, funnels and loops, and engagement/conversion/retention/referral mechanics.
• Deep expertise working with clickstream/event data and metrics.
• Experience designing and evaluating statistical tests, including multivariate tests with non-binary outcome variables.
• Well-versed in SQL and familiar with Python, R or other statistical packages.
• Confident in interacting with complex and nuanced data models, and will push for simplicity when necessary.
• Strong presentation and communication skills, with experience working with cross-functional stakeholders and executives.
• Familiarity communicating with and liaising between technical colleagues (Data Engineering, Machine Learning) as well as non-technical partners (User Research) and stakeholders (PMs).
• Comfortable extensively using BI tools (Looker preferred).
• Ability to thrive in a fast-paced, dynamic environment and drive change.