{"id":2339881,"url":"https://alion.io/job/airasia-data-scientist-2","title":"Data Scientist","company":{"id":1555,"name":"AirAsia","domain":"airasia.com","url":"https://alion.io/company/airasia","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":{"grade":"A","score":86,"open_postings":4,"ghost_share":0,"stale_share":0.75,"repost_share":0,"time_to_fill_p50_days":20,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sepang, Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":34000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":865},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"BigQuery","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SHAP","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vertex AI","optional":false},{"name":"XGBoost","optional":false},{"name":"AI Agents","optional":true},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"Go","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LLM","optional":true},{"name":"LLM Evaluation","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"NeuralProphet","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"PyCaret","optional":true},{"name":"Structured Outputs","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-09-12T00:00:00Z","employer_posted_date":"2026-09-12","last_verified_at":"2026-10-17T18:31:03Z","board_verified":true,"closed_at":null,"days_open":35,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":35},"description":"Job Description\nDuties and Responsibilities\nImprove models and algorithms to further optimize business outcomes.\nWork across the following areas:\nExploratory analysis: use data to suggest and prove hypotheses\nModeling: build optimization / predictive / statistical models to learn from data and estimate the unknowns - demand and sales forecasting, dynamic pricing for ancillary products, and demand planning\nData operations: query data, deploy models and automate pipelines in cloud\nSet up sound time-based validation and honest baselines, and prove a model beats them before it ships.\nWrite clean, reviewable Python and SQL, merged through proper code review.\nHelp analyze live experiments and learn to spot a misleading readout.\nCommunicate findings clearly to technical and non-technical stakeholders.\nDocument work so a teammate can run and extend it without you.\nWorking with commercial teams to maximize the revenue by infusing AI & ML in their systems.\nRequirements and Qualifications:\nBS in Physics, Mathematics, DataScience or Engineering discipline Up to 4 yrs relevant experience beyond first degree\nExperience with common data science toolkits, programming languages (.py), visualisation tools and SQL/NoSQL databases.\nMachine and Deep Learning :\nExperience building production ML systems, beyond notebooks and Kaggle competitions.· Solid understanding of machine learning algorithms, XGBoost, LightGBM, neural networks, decision trees, with a clear grasp of why you tuned what you tuned.· \nStrong Python and hands-on experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.· \nDemonstrable understanding of forecasting and regression pitfalls - lag feature leakage, target leakage in cross-validation, high-cardinality categorical handling, and the trade-offs between MAE, MAPE, and RMSE.· \nAbility to interpret models - SHAP, partial dependence, residual diagnostics - and explain results to non-technical stakeholders without dumbing them down.· \nHands-on Google Cloud Platform experience, particularly BigQuery (window functions, partitioning, cost-aware SQL) and Vertex AI (training jobs, model registry, endpoints, pipelines).· \nExperience with propensity / take-up (purchase-probability) models and probability calibration is a plus.· \nExposure to time-series forecasting at scale (many related series), probabilistic forecasts, or demand that builds up toward a deadline is a plus.· \nNice-to-have: deep learning for tabular and time-series problems (TFT, N-BEATS, NeuralProphet, TabPFN, Chronos); AutoML tooling such as PyCaret for rapid baselining.\nAlgorithm Engineering :\nStrong ability to implement, improve, and deploy ML and mathematical models in Python (Golang a plus for performance-critical services).· \nExperience productionizing models end-to-end, from SQL feature pipelines to deployed serving endpoints, on GCP using Vertex AI and BigQuery.· \nConduct systems tests for security, performance, and availability of deployed models.·\nDevelop and maintain design documentation, error analysis runbooks, and troubleshooting guides.· \nGit-based workflows, CI/CD discipline, and code review hygiene.· \nMonitoring discipline : drift detection, data quality checks, model performance tracking in production.· \nNice-to-have: experience with LLM-based or agentic tooling (LangGraph, MCP servers, prompt engineering for structured outputs, eval harnesses for LLM systems)\nWe are all different - one talent to another - that is how we rely on our differences. At AirAsia, you will be treated fairly and given all chances to be your best.We are committed to creating a diverse work environment and are proud to be an equal opportunity employer.\nSearch Firm Representatives - AirAsia does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place will be deemed the sole property of our company. 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