{"id":4210216,"url":"https://alion.io/job/riyom-technologies-data-scientist-3","title":"Data Scientist 3","company":{"id":4441648,"name":"Riyom Technologies","domain":"riyomtech.com","url":"https://alion.io/company/riyom-technologies","size_band":"51-200","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Power BI","optional":true}],"status":"live","first_seen_at":"2026-11-13T00:35:15Z","employer_posted_date":null,"last_verified_at":"2026-11-13T00:35:15Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for an experienced AWS Data Scientist to drive data-driven innovation through advanced analytics, Machine Learning, Generative AI, and AWS Cloud technologies. The ideal candidate should have strong experience in AWS data architecture, ML model development and deployment, MLOps, and modern AI technologies.\n\nResponsibilities: \nDesign and implement scalable AWS Data Lake and data processing architectures.\nDevelop and optimise solutions using Amazon Redshift.\nBuild data processing and analytics solutions using Python and SQL.\nWork with AWS services including S3, Lambda, Athena, Glue, Step Functions, and CloudWatch.\nDevelop, deploy, and monitor Machine Learning models on AWS.\nImplement MLOps practices for model deployment, monitoring, and lifecycle management.\nWork with Amazon SageMaker, Bedrock, and Redshift for AI and ML solutions.\nDevelop Generative AI and LLM-based applications using RAG and related techniques.\nCollaborate with data engineering, software engineering, and business teams to deliver data-driven solutions.\nMaintain code repositories and infrastructure using GitHub and Terraform.\nEnsure solutions are scalable, secure, reliable, and aligned with business requirements.\n\nRequirements: \n10+ years of relevant experience in Data Science, Machine Learning, or related fields.\nStrong experience with AWS Data Lake Architecture.\nStrong knowledge of Amazon Redshift Architecture.\nProficiency in Python and SQL.\nHands-on experience with AWS S3, Lambda, Athena, Glue, Step Functions, and CloudWatch.\nExperience with GitHub and Terraform.\nStrong understanding of MLOps and Machine Learning model deployment.\nHands-on experience with SageMaker, Bedrock, and Redshift.\nExperience with Generative AI, LLMs, and RAG.\nStrong analytical and problem-solving skills.\n\nPreferred Skills: \nExperience with Docker and Kubernetes.\nKnowledge of CI/CD pipelines.\nExperience with Power BI or Amazon QuickSight.\nExposure to cloud-based data and AI solutions.\nSkills\nAWS Bedrock, MLOps, Python, 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