{"id":2200338,"url":"https://alion.io/job/remitly-senior-data-scientist","title":"Senior Data Scientist","company":{"id":6304,"name":"Remitly","domain":"remitly.com","url":"https://alion.io/company/remitly","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":88,"open_postings":24,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":42,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":176000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Ignite","optional":true},{"name":"Machine Learning","optional":true},{"name":"PyTorch","optional":true}],"status":"live","first_seen_at":"2026-10-09T21:12:14Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-12T18:10:33Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Job Description:\nAt Remitly, we believe everyone deserves the freedom to access, move, and manage their money wherever life takes them. Since 2011, we've tirelessly delivered on our promise to customers sending money globally, providing secure, simple, and reliable ways to manage their money, ensuring true peace of mind. Whether it's supporting loved ones back home, growing a business across continents, or pursuing new opportunities abroad, we're not just here to move money- we're here to move our global customers forward.We're looking for builders, reimaginers, and global thinkers who want to work at the intersection of technology, trust, and transformation. If that's you and you're ready to do the most meaningful work of your career-we invite you to join over 2,800 passionate Remitlians worldwide who are united by our vision to transform lives with trusted financial services that transcend borders.\nAbout the Role:\nRemitly is looking for a seasoned analytical and product-oriented Senior Data Scientist & Product Analyst to help shape the future of our customer experiences and product strategy for the High Value Sender Customer Segment. This role sits at the intersection of marketing, product, engineering, and data science.\nIn this role, you will identify opportunities to improve customer experiences, design experiments that inform product decisions, and connect marketing activities with downstream customer behavior. You will be responsible for investigating product performance, identifying root causes behind key business outcomes, and influencing product roadmaps. You will also strengthen experimentation practices across the broader analytics community, be a valuable contributor towards strengthening the data foundation, and help teams make confident decisions grounded in evidence. This is an opportunity for someone who enjoys moving between strategic thinking and hands-on analysis while helping establish a strong analytics culture in a growing fintech organization.\nWhat You will do in your job\nDiscover opportunities to improve our products\nAnalyze customer journeys, behavioral patterns, and funnel performance\nUncover unmet customer needs and opportunities to improve activation, conversion, engagement, and retention.\nTranslate findings into prioritized recommendations that influence the product roadmap.\nPartner with Product and Engineering on experimentation\nTurn product hypotheses into well-designed experiments plans.\nDefining success metrics, guardrails, sample sizes, and measurement plans.\nGuide instrumentation, evaluate results, and recommend whether to launch, iterate, or stop.\nAdvance experimentation rigor and culture\nDevelop reusable standards for experiment design, analysis, and decision-making.\nAddress challenges such as selection bias, multiple testing, and heterogeneous treatment effects.\nMentor analysts and build shared practices through training, peer reviews, and practical tools.\nConnect marketing activities with product experiences\nExamine how acquisition channels, campaigns, targeting, and messaging influence customer intent and subsequent product behavior.\nIdentify where marketing promises and product experiences align or diverge, and recommend improvements across the customer lifecycle.\nApply statistical methods to consequential business questions\nUse causal inference, statistical modeling, and segmentation to understand drivers of customer behavior\nEstimate the impact of interventions when randomized experiments are impractical.\nPartner with Engineering and Analytics Engineering to improve instrumentation, data quality, and metric definitions, making product and growth measurement more reliable and reusable.\nCommunicate insights and influence decisions\nExplain findings, uncertainty, and tradeoffs clearly to technical and business audiences.\nHelp stakeholders turn analytical evidence into concrete product and investment decisions.\nWhat you will bring\nDemonstrated experience in product data science or analytics, independently leading complex work from problem definition through recommendation and measured impact.\nStrong expertise in experimental design, hypothesis testing, statistical inference, and causal inference, including their practical limitations.\nAdvanced SQL skills and proficiency in Python or R for analysis and statistical modeling.\nStrong product judgment and customer curiosity, with the ability to identify valuable opportunities beyond an initial stakeholder request.\nExperience analyzing acquisition, activation, conversion, engagement, and retention across the customer lifecycle.\nA track record of partnering effectively with Product, Engineering, and Marketing to influence priorities and decisions.\nClear communication skills, including the ability to distinguish evidence from assumptions and convey uncertainty.\nExperience mentoring analysts or data scientists and improving analytical standards across teams.\nA degree in a quantitative discipline or equivalent practical experience.\nMinimum Qualifications\n7+ years of experience in Product Analytics, Data Science, Decision Science, or a related analytical role.\nStrong expertise in SQL and experience working with large-scale datasets.\nExperience designing, executing, and analyzing experiments and A/B tests.\nProven track record influencing product decisions through data-driven insights.\nStrong analytical problem-solving and root cause investigation skills.\nExperience working closely with Product, Engineering, and Business teams.\nStrong understanding of statistical methods, hypothesis testing, and causal inference.\nExperience with Analytics and BI / Visualization tools (e.g., Tableau, Mode, Power BI, etc).\nExcellent communication and stakeholder management skills.\nPreferred Qualifications\nExperience in fintech, financial services, payments, lending, banking, or adjacent regulated industries.\nExperience applying Python, R, or other analytical programming languages to predictive analytics use-cases.\nExperience building product metrics frameworks and experimentation plans.\nFamiliarity with data modeling, data warehousing, and modern analytics engineering practices.\nExperience measuring and optimizing AI-powered products, features, and/or customer experiences.\nExposure to machine learning and AI applications.\nAI Expectation: The successful candidate will not only be comfortable using modern AI tools in their day-to-day analytical workflows but will actively seek opportunities to improve decision-making, experimentation, insight generation, and operational efficiency through responsible adoption of AI technologies. AI literacy and the ability to evaluate, implement, and measure AI-driven solutions are increasingly important expectations for this role.\nCompensation Details. The starting base salary range for this position is typically $176,000 to $220,000 USD. In the U.S., Remitly employees are shareholders in our Company and equity is part of our total compensation plan. Your recruiter can share more information about medical benefits offered, as well as other financial benefits and total compensation components offered with this role.\nOur Benefits:\nFlexible paid time off\nHealth, dental, and vision + 401k plan with company matching\nPaid parental, medical, military and family care leave\nMental Health & Family Forming Benefits\nEmployee Stock Purchase Plan (ESPP)\nContinuing education and travel benefits\nOur Connected Work Culture: Driving Innovation, Together\nAt Remitly, we believe that true innovation sparks when we come together. Our Connected Work Culture fosters dynamic in-person collaboration, where ideas ignite and challenging problems find solutions faster.\nUnder the Company's current hybrid-work expectations, employees in this position work onsite Tuesday through Thursday each week. Additional onsite attendance may be required based on business needs, and the Company may modify its hybrid-work expectations from time to time. These intentional in-office moments are vital for deepening relationships, fueling creativity, and ensuring your impact is felt where it matters most.\nRemitly is an E-Verify Employer\nAt Remitly, we are dedicated to ensuring that our workplace offers equal employment opportunities to all employees and candidates, in full compliance with applicable laws and regulations.\nRemitly is an equal opportunity employer. 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