{"id":63811,"url":"https://alion.io/job/mastercard-senior-data-scientist-ai-engineering","title":"Senior Data Scientist, AI Engineering","company":{"id":252,"name":"Mastercard","domain":"mastercard.com","url":"https://alion.io/company/mastercard","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":94,"open_postings":233,"ghost_share":0.017,"stale_share":0.352,"repost_share":0.099,"time_to_fill_p50_days":21,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Dublin, Ireland"],"countries":["IE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":100000,"max_usd":196000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":10},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-08-19T00:00:00Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-13T00:07:32Z","board_verified":true,"closed_at":null,"days_open":55,"trust":{"level":"ok","repost_count":2,"flags":["repost"],"days_open":54},"description":"Our Purpose\nMastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.\nTitle and Summary\nSenior Data Scientist, AI EngineeringOverviewMastercard's AI Centre of Excellence is building the next generation of AI capabilities powered by large-scale transaction data, machine learning, and foundation models. We are transforming how AI solutions are developed by enabling teams to leverage reusable learned intelligence rather than building bespoke feature-engineering pipelines for every use case.\nWe are seeking a Senior Data Scientist, AI Engineering to develop advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and applied machine learning to deliver measurable business impact. The successful candidate will partner closely with engineering, product, and business teams to bring innovative AI solutions from concept to production.\nWhat You'll Work On\nThis role focuses on applying machine learning, predictive modelling, and foundation-model representations to solve business problems at scale. Typical use cases include forecasting, propensity modelling, recommendation systems, behavioural analytics, and customer intelligence.\nWhile familiarity with Generative AI is beneficial, this is primarily an applied machine learning and data science role rather than a conversational AI, RAG, or agentic systems engineering position.\nRole / Key Responsibilities\nDesign, develop, and deploy machine learning solutions that solve high-impact business problems.\nDefine modelling approaches, experimentation methodologies, and success metrics for AI initiatives.\nApply foundation-model embeddings and modern machine learning techniques to improve model performance and accelerate development.\nDrive projects from problem definition through model development, deployment, and impact measurement.\nDevelop robust evaluation frameworks and benchmark new approaches against existing solutions.\nPartner with business, product, engineering, and analytics teams to identify and prioritise opportunities.\nCommunicate technical findings and recommendations to both technical and non-technical stakeholders.\nContribute to the development of best practices, reusable assets, and modelling standards across the AI organisation.\nSupport and mentor junior data scientists through technical guidance and knowledge sharing.\nAll About You\nRequired Experience\nProven experience developing and deploying machine learning solutions in production environments.\nExperience solving predictive modelling problems such as attrition, forecasting, recommendation systems, propensity modelling, fraud detection, risk modelling, or customer analytics.\nStrong track record of delivering measurable business outcomes through machine learning.\nExperience working in cross-functional teams to bring data science solutions from concept to deployment.\nRequired Technical Skills\nStrong expertise in machine learning, predictive analytics, statistical modelling, and experimentation.\nAdvanced Python and SQL skills.\nExperience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.\nStrong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection.\nExperience with feature engineering, representation learning, embeddings, and downstream machine learning workflows.\nFamiliarity with transformer-based models and foundation-model applications.\nExperience working with Databricks, Spark, Azure, AWS, or GCP.\nLeadership & Communication\nStrong analytical problem-solving skills.\nAbility to influence stakeholders through technical expertise and data-driven recommendations.\nExcellent communication and collaboration skills.\nAbility to translate complex technical concepts into actionable business insights.\nMinimum Qualifications\nBachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.\n5+ years of experience in machine learning, data science, AI, or advanced analytics.\nExperience developing and deploying machine learning models in production environments.\nDemonstrated experience applying statistical and machine learning techniques to real-world business problems.\nPreferred Qualifications\nMaster's degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Mathematics, or a related field.\nExperience with foundation models, embeddings, or representation learning.\nExperience in financial services, payments, banking, fintech, fraud, marketing analytics, or customer intelligence.\nPublications, patents, conference presentations, or other evidence of technical thought leadership.\nCorporate Security Responsibility\nAll activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:\nAbide by Mastercard’s security policies and practices;\n\nEnsure the confidentiality and integrity of the information being accessed;\n\nReport any suspected information security violation or breach, and\n\nComplete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.","description_format":"text","description_chars":5755,"description_truncated":false,"requirements":{"experience_years_min":5,"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":["Cards & Card Issuing","Payment Processing & 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