Role Description Point is transforming how we use data — from a team that reports what happened to one that explains why and recommends what to do next. As Lead Data Analyst, you'll be the most senior analyst on the team and the standard-bearer for that shift. You'll take our hardest, highest-stakes business questions and drive them from an ambiguous ask to a rigorous, trusted answer with a clear recommendation. Working closely with leaders across product, marketing, and operations, you'll own how our most important metrics are defined and set the bar for what great analysis looks like. This is a lead individual-contributor role with a potential direct report, helping build a function that's becoming a true analytical partner to the business — and the human judgment layer on top of a company increasingly able to self-serve with AI. Your responsibilities - Own the definition and integrity of core business metrics — bring an opinionated, well-reasoned point of view and drive alignment across stakeholders on a single source of truth. - Lead end-to-end deep-dive analyses on our highest-stakes questions — from framing the problem, through causal and statistical rigor, to a written recommendation the business can act on, including retrospective reads on whether past bets paid off. - Design and interpret experiments and causal analyses — separate correlation from causation, and quantify the tradeoffs and elasticities leaders need to prioritize with confidence. - Serve as an embedded analytical partner to senior product, marketing, and operations leaders — understand their goals, anticipate the questions, and proactively surface insights rather than just fielding requests. - Translate business logic into documented metric definitions and the semantic layer that powers self-serve analytics and AI-driven data access. - Set the analytical standard for the team — model rigorous, reproducible work and raise the bar through mentorship and example. Qualifications - 8+ years in analytics, data science, or a quantitative decision-science role, with a track record of analyses that changed business decisions — not just dashboards. - Deep SQL expertise and warehouse fluency (Snowflake and dbt a plus); comfortable navigating messy, imperfect data and reasoning rigorously about its reliability. - Strong statistical foundation — causal inference, experimentation, regression — and the judgment to know which method fits the question. - Exceptional at framing ambiguous problems and communicating findings crisply to senior, non-technical stakeholders; you form a point of view and defend it with evidence. - A track record of influencing decisions without formal authority, and a natural standard-setter who elevates the people around you. Requirements - Bonus: experience in fintech, lending, mortgage, or real estate; and hands-on experience with AI-assisted analytics (LLMs, semantic layers, self-serve tooling). Benefits - Generous health benefits: We provide comprehensive medical, dental, and vision plans with options for flexible spending accounts (FSA) and health savings accounts (HSA). - Unlimited paid time off: Recharge with unlimited paid time off and 10 company holidays. - Flexible remote and onsite work: Our teams work from many different locations and time zones. We support fully remote work and also have an amazing in-person environment in our downtown Palo Alto, CA HQ. - Fully paid parental leave: Point will supplement state Paid Family Leave (PFL) so employees receive 100% of their regular base pay, plus two additional weeks of fully paid leave after state PFL ends. In states without PFL, Point offers up to 8 weeks of paid parental leave. In addition, employees also receive 4 weeks of fully paid transition time, during which you may work 2–3 days per week while receiving full base pay. - Equity: We offer meaningful equity because we believe in sharing the value you help create. Your contributions directly impact our growth, and your equity gives you a stake in our future success. - Financial wellness: We provide 401K retirement plans for employees as well as guaranteed life insurance and short- and long-term disability coverage. - Extra work/life benefits: We provide monthly stipends for internet, mobile plans, wellness perks, a one-time home office reimbursement, and company provided equipment including a MacBook and monitor.

• Review, evaluate, and accurately label audio recordings and other data files using designated software tools and quality control procedures. • Inspect, classify, and analyze data according to established guidelines to determine quality, accuracy, and compliance. • Identify actual or potential quality issues, inconsistencies, anomalies, or irregularities and document findings with precision and attention to detail. • Communicate observations and quality concerns to team leads and escalate issues to management when necessary. • Maintain accurate records of quality assessments, findings, and related activities. • Assist with quality control projects and initiatives as assigned. • Collaborate effectively with team members to support operational goals and project success. • Contribute to process improvement efforts by identifying trends, recurring issues, and opportunities to enhance quality standards. • Consistently apply established rules, procedures, and quality criteria when evaluating data. • Complete QC Analyst basic certification training and testing. Following certification, exercises professional judgment and discretion to make independent and consequential risk determinations under defined time constraints. • Perform additional related duties as required.

• Generate policy-relevant analytical outputs on learning quality and equity using AMPL datasets, working together with country teams as co-authors. • Strengthen national capacity to independently apply advanced statistical methods to learning assessment data in selected countries. • Implement a six-month phased programme combining structured training, hands-on application and technical mentoring, centred on two in-person workshops. • Assess the availability and readiness of AMPL datasets and develop a common analytical framework addressing key policy questions on learning outcomes, equity and school/system-level effects. • Prepare training materials covering advanced statistical methods supported by practical tools such as annotated code and replicable templates.

• Analisar dados para a tomada de decisões • Colaborar com equipes para entender necessidades de dados • Auxiliar na implementação de soluções de dados