{"id":3610670,"url":"https://alion.io/job/swiftly-senior-data-scientist","title":"Senior Data Scientist","company":{"id":4224,"name":"Swiftly","domain":"goswift.ly","url":"https://alion.io/company/swiftly","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Argentina"],"countries":["AR"],"hiring_countries":["AR"],"hiring_countries_total":1,"salary":{"min":7000,"max":8000,"currency":"USD","period":"month","gross":null,"usd_annual":96000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Claude","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Grafana","optional":true},{"name":"LLM","optional":true},{"name":"NLP","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-11-02T13:53:41Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-05T08:59:29Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Position Summary:\nSwiftly is searching for a Senior Data Scientist to join our Data Science and Analytics team to build and ship machine learning models that power retail media and marketing measurements. This role will own data science projects end to end, from sourcing and shaping data in our Databricks lakehouse to developing models and delivering monitored, production-ready pipelines, with a strong understanding of the upstream data infrastructure and datasets that support machine learning. A key focus is marketing analytics: working closely with analytics and data engineering teams to measure and improve campaign performance across channels using approaches such as ROAS, incrementality testing, and marketing mix modeling. The ideal candidate is a curious problem solver who prioritizes data quality, observability, testing, and monitoring, collaborates well across teams, and is comfortable leveraging AI tools like Claude in their day-to-day work.\nThis is a full-time contract role. We use Deel as the employer of record and contract.\nResponsibilities Include:\nBuild, validate, and A/B test predictive models that drive marketing and shopper outcomes\nDevelop and improve campaign measurement approaches, including ROAS/iROAS, incrementality and holdout testing, and marketing mix modeling, and translate results into clear recommendations for business stakeholders\nOwn data science projects end to end: data sourcing, feature engineering, model development, business-friendly output, and a production machine learning pipeline\nSource and process large-scale, multi-tenant retail data using Python, Spark, and SQL in Databricks, including writing SQL and creating views and tables\nBuild and maintain upstream pipelines and well-modeled datasets that support downstream models, partnering with analytics and data engineering teams to define data contracts, quality expectations, and shared metric definitions\nImplement testing, data observability, and monitoring across machine learning and data pipelines, including data quality, model performance, and drift checks\nCreate dashboards and alerts for model, pipeline, and data monitoring\nPartner with Data Analysts and Data Engineers to answer data questions, offload repeatable processes, and help ensure reports are accurate\nProactively identify failure points, own the whole process, and solve complex data and pipeline issues\nLeverage AI tools (such as Claude) in day-to-day work to improve productivity and quality\nParticipate in a rotating on-call schedule\nOther related duties as assigned\nRequired Qualifications:\n5+ years of professional experience across data science, applied machine learning, and data engineering, with strong Python, SQL, and Spark skills, including hands-on experience working in Databricks\nHands-on experience developing marketing or advertising models, such as campaign measurement (ROAS, incrementality), marketing mix modeling, attribution, or audience/propensity and uplift modeling\nExperience building, deploying, and monitoring predictive and machine learning models in production\nStrong foundation in statistics and experimental design (e.g., hypothesis testing, regression, causal inference)\nStrong understanding of data modeling, data pipelines, and ETL processes, with hands-on experience building the views, tables, and transformations that support machine learning models and analytics\nB.S. in Mathematics, Statistics, Computer Science, Computer Engineering, or a related field\nOperational experience working with large-scale data warehouses and/or data lakes\nProven ability to collaborate with data analysts, data engineers, and internal stakeholders, and to work in an ambiguous, fast-paced environment\nAbility to leverage AI tools in day-to-day work\nBuild data products that are well-modeled, documented, and easy to understand and maintain \nPreferred Qualifications:\nExperience in marketing, retail, CPG, e-commerce, or retail media/ad tech\nExperience designing and analyzing A/B tests, holdout and geo experiments, and incrementality studies\nExperience with Databricks platform capabilities \nExperience with LLM, embedding, or NLP-based approaches (e.g., product classification or matching), including using tools such as Claude\nExperience with data visualization, observability and monitoring dashboards (e.g., Grafana or Databricks SQL dashboards or Tableau)\nExperience with ad-hoc analysis and data visualization","description_format":"text","description_chars":4426,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Argentina","iso":"AR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Public Transport","Smart 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