{"id":2496533,"url":"https://alion.io/job/binance-algorithm-engineer-market-growth-2","title":"Algorithm Engineer, Market Growth","company":{"id":44,"name":"Binance","domain":"binance.com","url":"https://alion.io/company/binance","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Hong Kong","Singapore","Australia","Taiwan"],"countries":["HK","SG","AU","TW"],"hiring_countries":["CN","IN","JP","AU","ID","MY","NZ","PK","PH","KR","TW","TH","VN","AS","BD","BT","BN","KH","CK","TL","FJ","PF","GU","KI","LA","MV","MH","MN","NR","NP","NC","NU","NF","MP","PW","PG","PN","WS","SB","LK"],"hiring_countries_total":47,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Flink","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-14T02:26:59Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-14T04:51:06Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, and more. Our mission is to increase the freedom of money and financial access for people around the world.\nAbout the Role\nIn this role, you will be responsible for developing and optimising core algorithmic models in marketing scenarios, including user behaviour prediction, profiling, ROI estimation, and traffic allocation strategies. You will design and build precision marketing models such as CTR/CVR prediction, LTV forecasting, and channel attribution analysis, leveraging user profiles, real-time behavioural data, and business objectives. A key part of the role will be creating data-driven strategies for user acquisition, retention, and repurchase, while continuously validating and improving performance through A/B testing, causal inference, and attribution analysis. You will collaborate closely with data, product, and operations teams to ensure these algorithms are effectively deployed within Binance’s marketing systems to drive measurable growth.\nResponsibilities:\nResponsible for core algorithm models in marketing scenarios, including but not limited to user behavior prediction, user profiling, ROI estimation, and traffic allocation strategies, to improve marketing efficiency and conversion rates.\nBuild precision marketing models (such as CTR/CVR prediction, LTV forecasting, marketing channel attribution analysis, etc.) based on user profiles, real-time behavioral data, and business objectives.\nDesign data-driven algorithm strategies for user lifecycle management (acquisition, retention, repurchase) to optimize user growth and operational performance.\nDeeply understand business needs and continuously track algorithm performance; validate and optimize models through A/B testing, causal inference, and attribution analysis, ensuring ongoing iteration and business impact.\nCollaborate closely with data, product, and operations teams to drive the implementation of algorithms in marketing systems (e.g., user growth initiatives).\nRequirements:\nAt least 3 years of experience in related fields, with a solid foundation in algorithms and programming.\nMaster’s Degree or above in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related disciplines.\nProficient in at least one programming language such as Python, Scala, or Java; familiar with big data processing frameworks like Hadoop, Spark, or Flink.\nStrong understanding of machine learning algorithms (e.g., LR, GBDT, DNN), commonly used models in marketing scenarios (e.g., Uplift Model, Lookalike), and tools such as TensorFlow or PyTorch.\nFamiliar with SQL/Hive and experienced in large-scale data cleaning, feature engineering, and model tuning.\nDeep understanding of user growth, ad placement, and e-commerce marketing scenarios, with the ability to design algorithm solutions aligned with business goals.\nClear logical thinking, ability to work independently, and strong team collaboration and communication skills.\nWhy Binance\nShape the future of finance \nCollaborate with world-class talent in a user-centric global organization with a flat structure\nTackle challenging projects in a fast-paced and innovative enviornment with autonomy\nThrive in a results-driven workplace with opportunities for career growth and continuous learning\nCompetitive salary and company benefits\nRemote-first, work-from-home arrangement (may vary depending on the nature of the role and team)\nBinance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.\nBy submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.\nWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. 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