About Tala
Tala is AI-native credit infrastructure for the global majority, combining proprietary risk intelligence with an expanding network of capital and distribution partners to power credit access at scale. Backed by more than $500 million in funding, Tala has distributed more than $7 billion in capital to more than 13 million customers across Africa, Latin America, and Asia—building one of the most robust datasets on thin-file borrowers anywhere in the world. Our mission is simple yet bold: to unleash the economic power of the global majority. We are looking for daring, data-driven leaders passionate about building the trust and credit infrastructure for the global majority.
Our pioneering work and proven impact have earned us consistent recognition, including being named to:
CNBC’s Disruptor 50 for five years.
CNBC’s World's Top Fintech Companies for two consecutive years.
Forbes’ Fintech 50 list for nine consecutive years.
Visionary investors, persuaded by the economic power of the global majority, have committed half a billion dollars in equity and debt to Tala's success.
Given the global nature of our team, we operate on a remote-first approach with office hubs in Santa Monica, CA (HQ); Nairobi, Kenya; Mexico City, Mexico; Manila, the Philippines; and Bangalore, India.
Most Talazens join us because they connect with our mission. If you are energized by the impact you can make at Tala, we’d love to hear from you!
The Senior Product Analyst is a strategic partner to Product, Engineering, and Design, responsible for shaping product direction through rigorous analysis, strong product intuition, and deep ownership of metrics, instrumentation, and experimentation. This role combines analytical depth with product thinking, enabling teams to understand user behavior, validate hypotheses, identify growth opportunities, and make high-quality decisions at speed. The Senior Product Analyst operates autonomously, leads analytical strategy for their product area, and ensures that the product team has a robust, batteries-included analytical foundation.
Product Strategy and High-Context Insight
Partner with Product Managers to influence roadmap priorities through structured problem framing and opportunity sizing.
Drive end-to-end analytical discovery: define questions, shape hypotheses, perform root-cause analysis, and identify second-order effects.
Produce high-context, narrative-driven analysis that shapes product decisions—not just dashboards or metrics reporting.
Identify long-term analytical needs and proactively set the direction for how the product should be measured.
Metrics Architecture and Observability
Own the metric hierarchy for the product domain (north-star, input metrics, counter-metrics, diagnostic metrics).
Design tracking plans and instrumentation schemas; work with engineering to ensure correct implementation.
Implement automated alerting and monitoring to surface health issues, funnel breaks, outliers, and behavior shifts in real time.
Experimentation and Causal Inference
Lead the design, execution, and interpretation of experiments (A/B tests, multivariate tests, staggered rollouts).
Select and apply appropriate statistical techniques (frequentist/Bayesian, CUPED, time-series methods).
Evaluate experiment readiness, calculate required sample sizes, and estimate expected effects.
Translate experiment outcomes into clear recommendations for product and business stakeholders.
Analytical Leadership and Collaboration
Mentor and support junior analysts; set standards for analytical depth, clarity, and rigor.
Act as the analytical owner in cross-functional initiatives, ensuring alignment on metrics and success criteria.
Influence how PMs and engineers adopt analytical best practices, instrumentation, and metric stewardship.
Communicate trade-offs, risks, and insights to both technical and non-technical audiences with precision.
Ownership of Analytical Assets
Partner with Analytics Engineering to ensure models, marts, and pipelines meet quality standards and SLAs.
Ensure the product area has a batteries-included analytical environment—well-documented, reliable, and easy to use.
Maintain data lineage, definitions, and documentation to minimize ambiguity and reduce analytical debt.
Experience
- 4-6 years in product analytics, data science, or growth analytics with extensive product-team experience.
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Proven track record influencing product roadmaps with evidence-based insights.
Experience in high-velocity experimentation environments (consumer apps, fintech, SaaS, marketplaces).
Technical Skills
Expert SQL; fluency with Snowflake or equivalent cloud data warehouses.
Strong experimental design and statistical analysis skills.
Familiarity with event-based instrumentation and telemetry platforms.
Competence with data visualization tools and dashboards (Looker, Metabase, etc.).
Analytical and Product Skills
Strong product intuition; ability to identify friction, opportunity, and causal drivers in user behavior.
Ability to articulate ambiguous or complex insights through structured narratives.
Experience diving into systems, logs, metrics, and data models.
Ability to operate autonomously and drive analytical strategy for a product domain.
Mindset
Relentless ownership and high standards.
Customer-obsessed and curious about system behavior.
Comfortable making decisions under ambiguity and imperfect data.
Proactive, not reactive: anticipates analytical needs before they surface.
Our vision is to build a new financial ecosystem where everyone can participate on equal footing and access the tools they need to be financially healthy. We strongly believe that inclusion fosters innovation and we’re proud to have a diverse global team that represents a multitude of backgrounds, cultures, and experience. We hire talented people regardless of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
