{"id":3744129,"url":"https://alion.io/job/procdna-analytics-lead-data-scientist-pharma-analytics-domain","title":"Lead Data Scientist - Pharma Analytics Domain","company":{"id":4465837,"name":"Procdna Analytics","domain":"procdna.com","url":"https://alion.io/company/procdna-analytics","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India","Noida, India","Delhi, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-04T11:29:12Z","employer_posted_date":null,"last_verified_at":"2026-11-04T11:29:12Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"About ProcDNA :\n\nProcDNA is a global consulting firm. We fuse design thinking with cutting-edge tech to create game-changing Commercial Analytics and Technology solutions for our clients. We're a passionate team of 470+ across 9 offices, all growing and learning together since our launch during the pandemic. Here, you won't be stuck in a cubicle. Instead, you'll be out in the open water, shaping the future with brilliant minds. Ready to join our epic growth journey?\n\nWhat are we looking for:\n\nWe are looking for a Lead Data Scientist who can own data science engagements end to end, from shaping the problem with the client to delivering and operationalizing ML solutions. You will lead a team of data scientists, guide technical decisions, and help grow ProcDNA's data science practice through client relationships and new capabilities.\n\nWhat you'll do:\n\n- Work with clients to translate business questions into well-scoped data science problems, and define the approach, data requirements and success measures.\n\n- Design and oversee ML solutions across the pharma commercial lifecycle, and choose methods that fit the data and the decision they support.\n\n- Own client communication and relationships and provide thought leadership to support their business decisions.\n\n- Quality-check the team's work and guide models to production through cross-team collaboration.\n\n- Lead project delivery across timelines, scope and team allocation, often across parallel engagements.\n\n- Mentor and manage a team of data scientists, and keep yourself and the team current with advancements in the field for collective growth.\n\n- Contribute to business development and internal capability building through proposals, POCs and reusable offerings, and help the practice grow.\n\nMust have :\n\n- 5.5+ years of hands-on experience in data science and ML, with at least 2 years leading projects or teams in a pharma consulting or client-facing setting.\n\n- A Bachelor's or Master's degree in engineering, statistics, mathematics or a relevant quantitative field.\n\n- Experience with life sciences data, such as claims (Komodo, IQVIA, Symphony), specialty pharmacy, CRM, DDD, Lab and other HCP, account or patient-level data.\n\n- Strong depth in Statistics, supervised and unsupervised ML, Deep learning and GenAI concepts, along with experience in deploying models to production.\n\n- Strong Python and SQL, with experience on distributed or cloud platforms such as Databricks, PySpark and AWS/Azure.\n\n- A track record of owning client communication and explaining results to non-technical stakeholders.\n\n- Experience in guiding and managing a team of data 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