{"id":456830,"url":"https://alion.io/job/amgen-data-science-manager","title":"Data Science Manager","company":{"id":4775,"name":"Amgen","domain":"amgen.com","url":"https://alion.io/company/amgen","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":85,"open_postings":349,"ghost_share":0,"stale_share":0.579,"repost_share":0.003,"time_to_fill_p50_days":42,"computed_at":"2026-10-26T05:57:25Z"}},"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":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-06-17T00:00:00Z","employer_posted_date":"2026-06-17","last_verified_at":"2026-10-24T16:13:48Z","board_verified":true,"closed_at":null,"days_open":131,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":131},"description":"Career Category\nEngineeringJob Description\nHOW MIGHT YOU DEFY IMAGINATION?\nIf you feel like you’re part of something bigger, it’s because you are. At Amgen, our shared mission-to serve patients-drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies. We are global collaborators who achieve together-researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It’s time for a career you can be proud of.\nLive | What you will do\nBuild and maintain models that identify and prioritize HCPs based on factors such as treatment behavior, patient opportunity, prescribing patterns, referral dynamics, engagement history, channel responsiveness, and likelihood to act.\nProvide technical guidance and mentorship to data scientists, ensuring best practices in feature engineering, model development, validation, measurement, reproducibility, and business interpretation.\nPartner with brand, sales, field operations, global analytics, data engineering, and technology teams to ensure HCP models are business-relevant, scalable, explainable, and deployable into downstream systems.\nThrive | What you can expect\nAs we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.\nYou will be part of a collaborative analytics environment where data science is used to improve commercial decision-making, strengthen customer engagement, and help teams better understand patient and HCP needs.\nBasic Qualifications\n7 years of hands-on experience in predictive modeling, machine learning, and commercial analytics\nDemonstrated experience building predictive models for customer targeting, scoring, prioritization, and segmentation.\nStrong programming skills in Python and SQL, with experience working in Databricks, PySpark, or similar big data environments.\nStrong understanding of feature engineering, model validation, model performance evaluation, explainability, and business translation.\nAbility to convert ambiguous commercial questions into structured analytics problems, modeling approaches, and actionable recommendations.\nExperience with explainable ML techniques and the ability to communicate key model drivers to non-technical business stakeholders.\nStrong ownership mindset, structured problem-solving ability, and bias toward action in a fast-paced business environment.\nPreferred Qualifications\nExperience in life sciences, pharma, biotech, or regulated healthcare analytics environments.\nExperience working with large-scale healthcare and commercial datasets, such as claims, EMR, lab, Rx, patient longitudinal data, CRM activity, sales, call activity, and digital engagement data.\nDeep understanding of HCP analytics, including targeting, prioritization, segmentation, field force optimization, omnichannel engagement, patient opportunity sizing, and treatment journey analytics.\nExperience working with IT teams to deploy models into production or business workflows\nExposure to advanced methods such as uplift modeling, causal inference, graph/network analytics, and reinforcement learning, in commercial data 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