{"id":2011970,"url":"https://alion.io/job/current-senior-data-scientist","title":"Senior Data Scientist","company":{"id":58521,"name":"Current","domain":"current.com","url":"https://alion.io/company/current-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Welcome to the Jungle","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"BigQuery","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scala","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vertex AI","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-07-30T00:08:56Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T13:55:47Z","board_verified":true,"closed_at":null,"days_open":74,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":74},"description":"Join Current, a data-driven company, as a Senior Data Scientist. In this hands-on role, you will focus on machine learning modeling to build predictive models that enhance customer understanding, improve user experience, and optimize member acquisition and retention. Your responsibilities will include data analysis, model development and optimization, A/B testing, customer segmentation, and collaboration with cross-functional teams. You will also have the opportunity to work with the ML Engineering team to ensure efficient data pipelines and scalable model deployment.\nMissions\nDesign, develop, and deploy predictive classification and regression models, along with anomaly detection models and algorithms.\nConduct extensive exploratory data analysis (EDA), feature engineering, and data preprocessing to ensure high-quality input for machine learning models.\nCollaborate with cross-functional teams (Product, Engineering, Marketing) to integrate machine learning solutions into customer-focused strategies and processes.\nProfil recherché\n - Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch- Experience in feature engineering, model selection, and performance optimization\n- Expertise in SQL and working with large, complex structured and semi-structured datasets\n- 5+ years of experience in data science with a strong emphasis on machine learning modeling\n- Strong communication skills and ability to present findings to technical and non-technical stakeholders\n- Master’s or higher degree in Data Science, Computer Science, Statistics, or a related field is preferred\n- Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods\n- Experienced in designing, executing, analyzing, and reporting on experiments\n- Experience working in fintech, e-commerce, or other data-rich consumer-facing industries\n- Familiarity with Google Cloud Platform (GCP) services, particularly Vertex AI and Dataflow, for scalable data processing and model training\n- Experience with dbt for data modeling\n- Familiarity with BigQuery or other MPP (Massively Parallel Processing) databases\n- Experience using the Scala programming language for developing scalable and efficient data 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