{"id":1515293,"url":"https://alion.io/job/airswift-senior-data-scientist","title":"Senior Data Scientist","company":{"id":2751907,"name":"Airswift","domain":"airswift.com","url":"https://alion.io/company/airswift-com","size_band":"5000+","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":75,"open_postings":18,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-01T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Doha, Qatar"],"countries":["QA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":55000,"max_usd":144000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1536},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-09-29T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-01T13:26:53Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Job reference\n1281069\nLocation\nDoha, Qatar\nSector\nEnergy - Oil & Gas\nFunction\nIT & Telecoms\nEmployment type\nContract\nDate published\nSeptember 29, 2026\nPosition Title: Senior Data Scientist\nJob Purpose & Key Accountabilities\nThe Senior Data Scientist will play a leading role in shaping and executing the company's data science strategy, supporting its ambition to become a truly data-driven organisation. The position is responsible for driving innovation through advanced analytics, machine learning, generative AI, and agentic AI while delivering measurable business value across multiple operational and corporate functions.\nKey Responsibilities\nShape and deliver the data science strategy and execution roadmap in support of the company’s ambition to become a data-driven organisation.\nPromote advanced analytics, machine learning, generative AI and agentic AI to improve business insight, operational performance, safety, efficiency and decision-making.\nLead the development of high-value PoCs, MVPs and scalable data science solutions, ensuring clear business impact and adoption by end users.\nMaximise the value of geoscience, field operations, HSE, corporate planning, major projects & engineering and other enterprise data through robust analytics, modelling, data products and decision-support solutions.\nManage internal stakeholders and external vendors to ensure technically sound, production-ready, secure and governable data science delivery.\nJob Dimensions & Activities\nSafety, Communication & Working Environment\nThe role requires active contribution to a culture of safety, collaboration and continuous improvement while engaging effectively with both technical and non-technical stakeholders.\nUphold and role model the company’s core values, incident-free culture and approved behaviours.\nBuild team spirit, collaboration and a growth mindset across digital and business stakeholders.\nCommunicate clearly with peers, leaders and business teams, translating complex data science concepts into practical business language.\nMentor junior team members, provide technical guidance and contribute to the successful delivery of data science initiatives.\nStudy: Ideation & Experimentation\nLead analytical innovation through exploration, experimentation and validation of advanced data science and AI solutions.\nLead and build proof of concepts, prototypes, MVPs and use cases across advanced analytics, machine learning, big data, machine vision, generative AI and agentic AI.\nConduct data science studies through robust quantitative analysis, statistical modelling, experimentation and validation.\nDevelop analytical solutions that enable in-house use case development and business decision support.\nTranslate analytical findings into actionable recommendations, measurable outcomes and clear implementation options.\nUse Case: Envisioning & Conceptualisation\nCollaborate with business stakeholders to identify, frame and prioritise data science opportunities with strong business value.\nFrame use cases with business stakeholders by assessing value, feasibility, data readiness, risks and the most appropriate analytical or AI methodology.\nContribute to technology choices, platform strategy, solution architecture and prioritisation of data science opportunities under the leadership of the Lead Data Scientist.\nCreate technical specifications, model requirements, data requirements and integration needs for the technical scope of work.\nUnderstand enterprise data sources, perform queries and translate business requirements into scalable data-driven solutions.\nSupport market scouting, vendor engagement and Call for Tender technical evaluations, including assessment of vendors’ data science, AI and delivery capabilities.\nUse Case: Development\nProvide technical leadership and oversight throughout the end-to-end development lifecycle of analytics and AI solutions.\nSupervise, challenge and provide guidance on vendor-led and in-house data analytics, data science, AI and machine learning delivery.\nCoordinate with development leads, product owners, Scrum teams and business SMEs to resolve issues and maintain delivery momentum.\nOversee the e2e design and implementation of analytics models by the vendors, ensuring the required quality.\nContribute to MLOps practices including model versioning, deployment readiness, monitoring, retraining, performance tracking and drift management.\nSupport user acceptance testing and technical validation of models, dashboards, AI assistants and analytical products.\nExplain sophisticated data science concepts in an understandable manner.\nUse Case: Roll-Out & Adoption\nSupport successful deployment and user adoption of data science solutions across the organization.\nPromote adoption of data science products by technical departments and ensure users understand the value, limitations and correct use of delivered solutions.\nSupport transition from experimentation to project or use case mode, including deployment at scale and integration into business workflows.\nUse Case: Enhancements\nEnsure the continuous improvement and sustainability of deployed data science solutions.\nSupport model retraining, recalibration, enhancement based on changing data, user feedback and business needs.\nMonitor new analytical methods, AI techniques, software, hardware and platform trends relevant to the business.\nContribute to partnerships, standards and reusable methods that improve the maturity and sustainability of data science delivery.\nContext & Work Environment\nPosition located in Doha, Qatar.\nStandard office hours.\nFive working days per week.\nQualifications, Experience & Skills\nEducation: Master’s degree in a relevant field such as Data Science, Computer Science, Statistics, Mathematics, Engineering or a related quantitative discipline.\nMust Have Experience\nMinimum 8 years of experience in data science, advanced analytics and/or applied AI, with a proven track record of developing, validating and implementing machine learning models and data-driven decision solutions.\nExperience translating business problems into analytical use cases, defining success metrics, assessing data readiness and delivering measurable business value.\nIndustry experience in oil and gas or industrial operations, with understanding of operational, geoscience, production, reservoir, HSE and engineering data.\nHands-on experience with generative AI, LLM-based solutions, retrieval-augmented generation, prompt orchestration, and agentic AI workflows is an advantage.\nExperience with the machine learning lifecycle, including experimentation, validation, deployment readiness, monitoring, retraining, drift management and enhancement.\nTechnical & Soft Skills\nProgrammingStrong proficiency in Python is required.\nExperience with Spark or distributed processing is an advantage.\n\nData ProcessingStrong experience with SQL, Pandas and data preparation.\nExposure to data pipelines, data quality, metadata and structured or unstructured data processing.\n\nMachine LearningExperience with Scikit-learn, TensorFlow, PyTorch, XGBoost or similar frameworks.\nStrong understanding of statistical modelling, predictive analytics, validation and experimentation.\n\nMLOpsFamiliarity with production-ready ML practices such as:Version control\nModel tracking\nCI/CD concepts\nAPIs\nMonitoring\nRetraining\nDrift detection\nModel governance\n\nCloud & PlatformsHands-on experience with Microsoft Azure.\nExperience with Azure AI/Data Services, Databricks, lakehouse platforms or equivalent cloud-native data and AI services is an advantage.\n\nVisualisation & StorytellingProficiency in Power BI or similar visualisation tools.\nAbility to communicate insights, uncertainty, assumptions and recommendations to both technical and non-technical audiences.\n\nProblem-SolvingProven ability to structure ambiguous business challenges and convert them into practical, scalable and value-adding data science solutions.\n\nCollaborationStrong stakeholder management, vendor coordination and cross-functional collaboration skills.\nAbility to build trust and influence decisions through clear and transparent communication.\n\nNot the job you are looking for? Search hundreds more\nSearch Now.","description_format":"text","description_chars":8184,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Qatar","iso":"QA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-30T09:22:24Z"}],"liveness":{"score":36,"band":"fade","label":"Fading","p_open":1,"p_active":0.361,"p_room":1,"age_days":2,"expected_fill_days":23,"reasons":["conf:2","agency","stale_co","win:early","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/airswift-senior-data-scientist","json_url":"https://alion.io/job/airswift-senior-data-scientist.json","meta":{"generated_at":"2026-10-01T17:58:52Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":237,"day_limit":5000,"remaining_today":4763,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}