{"id":3271251,"url":"https://alion.io/job/xtremax-data-scientist-fraud-risk-analytics-public-sector","title":"Data Scientist - Fraud & Risk Analytics (Public Sector)","company":{"id":3414,"name":"Xtremax","domain":"xtremax.com","url":"https://alion.io/company/xtremax-pte-ltd","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":89,"open_postings":47,"ghost_share":0,"stale_share":0.255,"repost_share":0,"time_to_fill_p50_days":60,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":114000,"period":"year","method":"role_country_seniority_unknown","sample_n":108},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"CI/CD","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-10-26T11:48:05Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-31T13:11:04Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"At Xtremax, we're looking for a Data Scientist to strengthen fraud-risk analytics and improve the reliability of models used to detect misuse of public training subsidies. You'll work with a Data Science and AI team responsible for enhancing existing risk models, evaluating their performance and extending fraud-risk coverage to new schemes.\nYour work will combine statistical analysis, model validation, feature development and practical implementation. You'll review model methodologies and thresholds, investigate performance trade-offs, and develop monitoring that accounts for real-world challenges such as imbalanced datasets and delayed or incomplete investigation outcomes.\nYou'll collaborate with engineers, analysts and programme stakeholders to turn business and policy requirements into measurable risk indicators and defensible analytical decisions. The role offers an opportunity to deepen your experience in applied data science while contributing to maintainable analytics and stronger in-house technical capability.\nResponsibilities\nReview and recalibrate fraud-risk model methodologies and thresholds through back-testing, impact assessments and validation.\nEnhance fraud-risk scenarios, indicators, features and analytical logic based on business, policy and scheme requirements.\nEvaluate model performance using precision, recall and other appropriate measures, balancing detection effectiveness with operational impact.\nBuild and improve technical dashboards for model performance, data drift, concept drift and alerting.\nDevelop performance measures that account for delayed, incomplete and evolving investigation outcomes.\nAssess new schemes by analysing eligibility rules, claims processes, scheme structures and potential fraud patterns.\nMap emerging risks against existing fraud-risk taxonomies and recommend how new schemes can be incorporated into model coverage.\nAnalyse complex datasets, investigate anomalies, assess data quality and document assumptions and data lineage.\nCommunicate analytical findings, limitations, trade-offs and recommended actions to technical and non-technical stakeholders.\nMaintain reproducible analytical code, methodology records and technical documentation, and transfer knowledge to the internal team.\nRequirements\nDegree or diploma in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative discipline.\nTypically 3-5 years of experience in data science, advanced analytics, model validation, fraud/risk analytics or programme analytics.\nStrong hands-on proficiency in Python and SQL for data extraction, transformation, analysis and reproducible workflows.\nExperience developing, validating or enhancing predictive, risk-scoring, fraud-detection or anomaly-detection models.\nUnderstanding of feature development, back-testing, threshold calibration and model performance evaluation.\nAbility to translate business, policy or operational requirements into analytical specifications, risk indicators and measurable hypotheses.\nExperience working with complex datasets, including data-quality assessment, anomaly investigation and documentation of analytical assumptions.\nStrong analytical reasoning, attention to detail and structured problem-solving skills.\nClear written and verbal communication, including the ability to explain analytical results and trade-offs to non-technical stakeholders.\nPreferred\nExperience working with imbalanced data and delayed, incomplete or evolving outcome labels.\nExperience with model monitoring, data drift, concept drift and alert thresholds.\nExperience developing dashboards in Tableau or equivalent platforms.\nFamiliarity with CI/CD, MLOps or operational deployment of analytical models.\nExperience with Spark, PySpark, AWS Redshift or AWS Glue.\nKnowledge of network or graph analytics for identifying related entities and coordinated patterns.\nExperience with workforce, training, grants, claims or regulatory datasets.\nFamiliarity with Singapore public-sector data governance and classification requirements.\nBenefits\nBy submitting your resume/CV, you consent and agree to allow the information provided to be used and processed by or on behalf of Xtremax Pte Ltd for purposes related to your registration of interest in current or future employment with us and for the processing of your application for employment.\nYou also represent to us that you have obtained the consent of your referees when you disclose to us their personal data for the purpose of conducting reference checks.\nThe personal data held by us relating to your application will be kept strictly confidential and in accordance with the PDPA. You may also refer to our Privacy Policy for more details here:\nWe regret to inform you that should you not consent to providing the necessary data required for us to process your application, your application will be considered void.","description_format":"text","description_chars":4898,"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":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Government","IT Consulting & Digital Transformation","Managed IT Services (MSP)","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-26T11:48:05Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":60,"reasons":["conf:0","velocity","win:early"],"computed_at":"2026-10-31T05:58:55Z"},"pay":null,"html_url":"https://alion.io/job/xtremax-data-scientist-fraud-risk-analytics-public-sector","json_url":"https://alion.io/job/xtremax-data-scientist-fraud-risk-analytics-public-sector.json","meta":{"generated_at":"2026-10-31T14:39:06Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":22795,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3414},"rest":"https://alion.io/mcp/rest/get_company?id=3414"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fxtremax-data-scientist-fraud-risk-analytics-public-sector"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fxtremax-data-scientist-fraud-risk-analytics-public-sector"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fxtremax-data-scientist-fraud-risk-analytics-public-sector"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/xtremax-data-scientist-fraud-risk-analytics-public-sector\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fxtremax-data-scientist-fraud-risk-analytics-public-sector"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3271251}},{"tool":"search_jobs","arguments":{"company":"xtremax.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3271251},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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