{"id":91170,"url":"https://alion.io/job/arq-senior-data-scientist-growth","title":"Senior Data Scientist, Growth","company":{"id":450345,"name":"ARQ","domain":"arqfinance.com","url":"https://alion.io/company/arq-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":80,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":14,"computed_at":"2026-10-28T05:59:10Z"}},"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":["London, United Kingdom","New York, United States"],"countries":["GB","US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":87000,"max_usd":172000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":52},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-08-12T10:34:20Z","employer_posted_date":"2026-08-12","last_verified_at":"2026-10-28T10:33:13Z","board_verified":true,"closed_at":null,"days_open":77,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":77},"description":"What We’re Looking For\nWe're looking for a Senior Data Scientist to join ARQ's Growth team as our first data science hire - owning all data science initiatives across Growth and Marketing, starting with predicting customer lifetime value across our markets and acquisition channels. You'll report directly to the Head of Growth and our COO.\nYou’ll be responsible for developing, maintaining, and improving LTV prediction models across our four countries, helping us make sharper decisions on growth investment, channel performance, acquisition quality, and long term customer value.\nThis is a high ownership role for someone who has worked on consumer growth, LTV, acquisition, retention, or monetisation problems in a B2C or D2C environment. You should be comfortable taking ambiguous business questions, turning them into measurable modelling problems, and building solutions that influence real commercial decisions.\nWhat You’ll Be Doing\nDesign, build, maintain, and improve lifetime value prediction models across ARQ’s countries and acquisition channels.\n\nWork closely with Growth & Marketing, Product, Finance, Data Engineering, and Engineering teams to understand business needs and translate them into modelling solutions.\n\nHelp evaluate acquisition quality by channel, campaign, geography, customer segment, and product behaviour.\n\nBuild models that support better decisions around growth spend, payback periods, customer quality, retention, and long term value.\n\nAnalyse large scale customer, product, marketing, and transaction datasets to identify patterns, risks, and opportunities.\n\nContinuously monitor model performance and improve accuracy, reliability, and business impact over time.\n\nCreate clear frameworks and metrics that help teams understand the trade offs behind growth decisions.\n\nPartner with Data Engineering and Engineering teams to productionise models, pipelines, and reporting where needed.\n\nBring a pragmatic approach to modelling, balancing technical depth with commercial impact.\n\nOver time, contribute to other Data Science challenges across Growth and the wider business.\n\nWhat You’ll Need\n5+ years in Data Science, Machine Learning, Applied Statistics, Analytics, or a related discipline.\n\nExperience building prediction models in a consumer business (B2C, D2C), ideally around LTV, growth, acquisition, retention, churn, monetisation, or customer value.\n\nStrong Python skills and experience working with large scale datasets.\n\nSolid understanding of supervised learning techniques, model evaluation, feature engineering, and statistical trade offs.\n\nAbility to translate ambiguous commercial questions into structured data science problems.\n\nStrong business judgement and the ability to connect model outputs to real decisions.\n\nExperience working cross functionally.\n\nClear communication skills, especially when explaining modelling assumptions, limitations, and recommendations to non technical stakeholders.\n\nComfortable operating in a fast moving environment with high ownership and evolving priorities.\n\nFluent in English, as we collaborate with teams across the globe.\n\nNice To Have\nExperience in fintech, banking, payments, investing, lending, or another financial consumer product.\n\nExperience at a high growth B2C or D2C company, such as consumer fintech, health tech, subscription, retail, wellness, or marketplace businesses.\n\nExperience with LTV, CAC, payback period, acquisition efficiency, cohort modelling, retention modelling, churn prediction, or marketing mix related problems.\n\nExperience working across multiple countries, currencies, channels, or customer segments.\n\nExperience productionising models or working closely with Engineering and Data Engineering teams to deploy data science solutions.\n\nFamiliarity with MLOps, model monitoring, experiment design, causal inference, or incrementality measurement.\n\nBenefits\nCompetitive salary and benefits\n\nStock options, so you own part of what you build\n\nDiscretionary performance bonus\n\nThe latest tools and technology\n\nA world-class team that will challenge and grow your skills\n\nThe opportunity to help build the best fintech app in Latin America\n\nOffice Policy: 3-4 days a week in-office","description_format":"text","description_chars":4198,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":["Stock options"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"United 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