{"id":4188479,"url":"https://alion.io/job/saic-data-scientist-associate","title":"Data Scientist Associate","company":{"id":58788,"name":"SAIC","domain":"saic.com","url":"https://alion.io/company/saic","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":78,"open_postings":89,"ghost_share":0,"stale_share":0.854,"repost_share":0.011,"time_to_fill_p50_days":24,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Upper Marlboro, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Hadoop","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-12T17:19:31Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-13T02:30:22Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"SAIC is seeking a Data Scientist Associate with a strong background in statistical data analysis using modern analytic tools and frameworks. Experience with techniques and platforms to create, manage, manipulate, and draw insight from large datasets is desired. The candidate will join the dynamic team at the Identity and Data Sciences Laboratory (IDSL). The IDSL is tasked with evaluating how new AI technologies can be best integrated into operational use-cases across the US government. We are investigating how AI systems can improve process efficiency and effectiveness, be optimally teamed with human operators, and detect fraud. Our engineers enjoy a great work-life balance and work in an environment that promotes learning and exploration.\nResponsibilities:\nWork with senior data scientists to perform data management and analysis tasks.\nDevelop and apply extract, transform, load (ETL) data pipelines to create analytic datasets.\nPerform exploratory data analyses (EDA) on analytic datasets.\nApply AI models to datasets for AI evaluation, data enrichment, prediction, or generation.\nWork with senior scientists and engineers to develop statistically sound designs of experiment, defining and testing hypotheses.\nWork with senior scientists and engineers to plan and execute comprehensive statistical analyses to generate quantitative results.\nMaintain attention to detail and quality standards to ensure results are accurate and withstand technical scrutiny.\nContribute to ongoing data collection activities.\n Required:\nA bachelor’s degree in mathematics, statistics, data science, or a comparable quantitative science,\n0-2 years applicable professional experience \n Ability to obtain and maintain a public trust requiring US Citizenship.\nProficiency in programming statistical analyses, machine learning, and/or data mining (R, Python, or similar).\nProficiency in database technologies (SQL, NoSQL).\nFamiliarity with source control (e.g., Git).\nFamiliarity with common data formats (JSON, Parquet, XML, etc.).\n\nDesired:\nExperience with techniques and platforms to manage, manipulate, and draw insight from large datasets (Spark, Hadoop, Databricks, etc.).\nUnderstanding of scaling and performance of distributed/cloud systems (AWS).\nUnderstanding of machine vision, generative AI, machine learning, automation, and scripting.\nStrong communication skills, with the ability to present findings and recommendations to both technical and non-technical 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