{"id":666398,"url":"https://alion.io/job/amanotes-senior-data-scientist","title":"Senior Data Scientist","company":{"id":49497,"name":"Amanotes","domain":"amanotes.com","url":"https://alion.io/company/amanotes","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":85,"open_postings":24,"ghost_share":0.167,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":271,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ho Chi Minh City, Vietnam"],"countries":["VN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14000,"max_usd":36000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-07-02T04:47:23Z","employer_posted_date":"2026-07-02","last_verified_at":"2026-10-16T21:17:06Z","board_verified":true,"closed_at":null,"days_open":106,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":106},"description":"Objectives\nWe are looking for a Data Scientist with strong Machine Learning capability to design, validate, and productionize models that improve player experience and business outcomes across Amanotes games and data products.\nThis role will help Amanotes move from descriptive analytics to intelligent decisioning by turning user, product, and business data into ML-powered actions such as dynamic difficulty adjustment, recommendation, offer personalization, and ad optimization.\nWHAT YOU WILL DO\nWork on high-impact personalization and optimization use cases such as song recommendation, dynamic difficulty adjustment, ad frequency optimization, personalized IAP offers, churn prevention, and content or event performance prediction.\n\nBuild end-to-end ML workflows: problem framing, feature design, model development, offline validation, experiment design, online testing, monitoring, and iteration based on results.\n\nDevelop predictive models that support UA, Product, and business decisions, such as pUV/LTV prediction, early-value prediction, creative winning prediction, UA and portfolio ROI forecasting, and campaign or resource-allocation recommendation signals.\n\nPartner closely with UA and Product teams to turn predictive outputs into practical workflows for planning, targeting, bidding, creative iteration, and growth decision-making.\n\nExplore large-scale behavioral data to uncover player patterns, segments, and opportunities using statistical analysis, experimentation, and data science techniques.\n\nWork at the intersection of Data Science, Product, Game Design, and Music Experience Design to improve how music changes player experience inside Amanotes products.\n\nContribute to ML-driven systems for game difficulty and player flow, including difficulty prediction, game skill estimation, frustration detection, and next-best difficulty or assist recommendations.\n\nSupport Amanotes’ music-experience initiatives by helping quantify, model, and validate how music mechanics, reactive audio, or musicalized gameplay affect retention, engagement, monetization, and user experience.\n\nWork with Data Engineering to ensure the right data foundation, quality, and availability for model training, scoring, monitoring, and analysis.\n\nDesign and analyze A/B tests or other controlled experiments to measure model impact on engagement, retention, monetization, player experience, and product growth.\n\nCommunicate findings, trade-offs, and recommendations clearly to both technical and non-technical stakeholders.\n\nContribute to Amanotes’ broader data and AI capability by improving reusable data assets, experimentation practices, predictive systems, and data-science ways of working.\n\nQUALIFICATIONS\nBachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or another quantitative field.\n\nStrong foundation in statistics, experimentation, machine learning, and analytical problem solving.\n\nStrong hands-on ability with SQL and Python for data extraction, analysis, feature engineering, and modeling.\n\nExperience building data products or ML solutions end to end, from discovery and R&D to production or live experimentation.\n\nAbility to work with messy, large-scale behavioral data and convert it into usable features, insights, and decisions.\n\nComfortable working cross-functionally with product, engineering, and business stakeholders in an ambiguous, fast-changing environment.\n\nClear communication in English and Vietnamese, with the ability to explain technical topics to non-technical audiences.\n\nBENEFITS\nAt Amanotes, you will be enjoying the dynamic working environment with unique music culture many benefits as below:\nCompetitive salary upon experience\n13th-month salary\nYear-end Bonus\nFlexible working time\nPersonal learning and well-being budget\nTeam-building budget\nLunch and parking allowance\nVarious learning activities, including internal training & sharing, international conferences, and e-learning (Udemy, LinkedIn Learning...).\nEngaging music events: Music Night, Amasing Night, Music schools…\nEmployee Assistance Program to support mental health & well-being. \nMinimum 12 days of paid annual leave, plus 10 days of paid sick leave.\n12 days working from home per year.","description_format":"text","description_chars":4230,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"Vietnamese","level":"Upper-Intermediate (B2)","optional":false},{"language":"English","level":"Upper-Intermediate (B2)","optional":false}]},"benefits":["Annual leave","Flexible schedule"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Mobile Games","Audio & Music Software"],"lifecycle":[{"event":"open","at":"2026-09-10T21:58:37Z"}],"visa":[],"liveness":{"score":59,"band":"ok","label":"Likely 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