{"id":2557926,"url":"https://alion.io/job/recruteaction-senior-data-scientist-machine-learning-generative-ai","title":"Senior Data Scientist (Machine Learning & Generative AI)","company":{"id":3815017,"name":"Recruteaction","domain":"recruteaction.com","url":"https://alion.io/company/recruteaction-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"contractor","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":65,"max":75,"currency":"CAD","period":"hour","gross":null,"usd_annual":106000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CrewAI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Glue","optional":true},{"name":"AWS Lambda","optional":true},{"name":"AWS Step Functions","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-14T19:49:06Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-18T06:31:25Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Senior Data Scientist (Machine Learning & Generative AI)\nBring your passion for data, machine learning, and GenAI to the insurance sector for our client. Help transform complex business problems into practical, innovative solutions while contributing to advanced analytics initiatives that create value across Canadian business units.\nWhat is in it for you:\n\nSalaried: $65-75 per hour.\nIncorporated Business Rate: $77-87 per hour.\n12-month contract providing coverage for maternity leave.\nFull-time position: 37.50 hours per week.\nHybrid work arrangement with 3 days on-site, including Thursdays.\nResponsibilities:\n\nData Science and Machine Learning\n\nTranslate business goals into analytical problems and identify optimal algorithms, statistical techniques, and/or GenAI architecture suitable for the business problem at hand.\nWork in cross-functional teams to develop ML/data science products, including GenAI applications.\nApply best-in-breed data science techniques, including descriptive, predictive, and machine learning methods, from design to implementation.\nFocus on feature engineering, model training, model evaluation, and prompt engineering for LLMs.\nGenAI & Agentic AI Development \n\nDesign, develop, and deploy GenAI solutions, including AI agents, chatbots, and autonomous systems that solve complex business problems.\nResearch and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques, and agentic frameworks such as LangChain, LangGraph, and CrewAI.\nImplement AI bots/agents with advanced reasoning capabilities and tool-use patterns.\nWork with vector databases and embedding models to build intelligent information retrieval systems.\nTechnical Leadership & Collaboration\n\nBreak down broader data science development milestones into actionable goals, activities, and work plans.\nCreate and maintain technical design artifacts describing application functionality, data models, interfaces, and integrations.\nEngage and negotiate with stakeholders, make business recommendations, and effectively present findings to multiple levels of stakeholders.\nChampion continuous improvement and foster innovation within the analytics community.\nWhat you will need to succeed:\n\nRequired qualifications\n\nBachelor’s degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.\n5+ years of experience developing and implementing data science techniques.\nProficiency in Python for data science and GenAI application development.\nExperience writing complex SQL and PySpark queries to extract and integrate data from multiple database sources.\nProficiency in machine learning, including supervised and unsupervised models.\nDemonstrated experience in data transformation, data manipulation, and working with structured and unstructured data.\nStrong understanding of APIs, microservices architecture, and cloud-native development.\nHands-on expertise with GenAI frameworks and LLM APIs, including experience developing AI bots and agents with reasoning and tool-use capabilities.\nStrong understanding of Retrieval-Augmented Generation techniques, prompt engineering, and fine-tuning methodologies, with familiarity with vector databases and embedding models.\nExperience with chatbot development concepts and conversational AI design.\nReliability Clearance required.\nPreferred qualifications\n\nExperience with AWS services, including SageMaker, Lambda, Bedrock, and other AI and machine learning services.\nExperience with data warehousing, pipelines, and big data technologies such as AWS Glue for ETL, Glue Catalog, Glue Data Quality, and AWS Step Functions.\nSoft skills\n\nExceptional communication skills with technical and non-technical stakeholders.\nEffective and concise oral and written storytelling and insights communication skills.\nAn ability to manage multiple projects, changing deadlines, and priorities.\nAn ability to mentor and guide junior data scientists and data engineers.\nStrong problem-solving and analytical skills.\nKeen attention to detail.\nFierce curiosity for discovering and leveraging new data.\nAn inquisitive mind.\nA willingness to ask questions to help lead projects to commercial value.\nA willingness to recognize that innovation attempts can lead to failure.\nA passion for solving problems.\nA focus on efficient execution and delivery.\nA thirst for continuously updating data science knowledge.\nWhy Recruit Action? \n\nRecruit Action (agency permit: AP-2504511) provides recruitment services through quality support and a personalized approach. As part of the screening process, some applications may be reviewed using artificial intelligence tools. 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