{"id":68570,"url":"https://alion.io/job/oscilar-sr-staff-data-scientist","title":"Staff Data Scientist","company":{"id":3434,"name":"Oscilar","domain":"oscilar.com","url":"https://alion.io/company/oscilar","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":89,"open_postings":18,"ghost_share":0,"stale_share":0.222,"repost_share":0,"time_to_fill_p50_days":82,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US","CA"],"hiring_countries_total":2,"salary":{"min":210000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Dask","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-21T00:26:53Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-17T11:09:42Z","board_verified":true,"closed_at":null,"days_open":57,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":57},"description":"Shape the future of trust in the age of AI\nAt Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place.\nWhy join us:\nMission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer.\n\nOwnership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.\n\nInnovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.\n\nJob Description\nAs a Data Scientist at Oscilar, you will be responsible for developing and implementing advanced fraud detection models to protect our customers’ business from fraudulent activities. As an early member in the ML team you will have great impact in building out our ML stack.\nResponsibilities:\nDevelop and implement advanced fraud detection models, leveraging machine learning and statistical techniques, to identify and prevent fraudulent activities across our platform.\n\nCollaborate with cross-functional teams, including engineering, product, and operations, to design and implement fraud detection systems and processes.\n\nAnalyze large volumes of data to identify patterns, trends, and anomalies indicative of fraudulent behavior, and develop data-driven insights to improve fraud prevention strategies.\n\nEvaluate the performance of existing fraud detection models and systems, and continuously optimize and update them to adapt to changing fraud trends and tactics.\n\nStay up-to-date with the latest trends and advancements in fraud detection, data science, and machine learning, and apply this knowledge to enhance our fraud prevention capabilities.\n\nCommunicate complex data analysis and model performance results to both technical and non-technical stakeholders, driving data-driven decision-making across the organization.\n\nEnsure data privacy and security compliance in all aspects of fraud detection and data analysis.\n\nRequirements:\n5+ years of experience in data science, machine learning, or a related field, with a focus on fraud prevention and/or anti-money laundering.\n\nProficiency in Python.\n\nFluency in cloud development (AWS, GCP, Azure, etc.) and MLOps is a plus.\n\nStrong knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection.\n\nExperience working with large datasets using distributed systems like Apache Spark and Dask, handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale.\n\nExcellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data.\n\nStrong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences.\n\nAbility to work independently and collaboratively in a fast-paced, dynamic startup environment.\n\nPreferred Qualifications:\nExperience in the fintech, marketplaces, or financial services industry.\n\nKnowledge of current fraud tactics and trends, as well as experience with fraud detection tools and systems.\n\nBenefits\nCompensation: Competitive salary and equity packages, including a 401k\n\nFlexibility: Remote-first culture - work from anywhere\n\nHealth: Comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)\n\nBalance: Unlimited PTO policy\n\nTechnical: AI First company; 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