{"id":2856820,"url":"https://alion.io/job/novartis-director-advanced-analytics-modeling","title":"Director, Advanced Analytics & Modeling","company":{"id":5824,"name":"Novartis","domain":"novartis.com","url":"https://alion.io/company/novartis","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":79,"open_postings":60,"ghost_share":0,"stale_share":0.817,"repost_share":0.033,"time_to_fill_p50_days":30,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Analytics","role_family":"Analytics","seniority":"head","employment_type":"full_time","work_mode":"hybrid","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":28000,"max_usd":61000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":351},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Interpretability","optional":false},{"name":"NLP","optional":false},{"name":"Agile","optional":true},{"name":"Machine Learning","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-10-15T00:00:00Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-22T03:45:26Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Job Description Summary\nThe Director, AMM, is accountable for the Advanced Analytics & Modeling strategy, organization and portfolio, including strategic directions, capability evolution, capacity allocation, cross-capability orchestration, analytical quality, US delivery, and decision impact.The role holds established capability leaders accountable for differentiated roadmaps and outcomes and directly incubates AI & Unstructured Intelligence until sustained demand, maturity, and scale support a different LT model.\nThis role DOES NOT own the broader enterprise analytics strategy, enterprise analytics governance, technology architecture, analytics platforms, production engineering, or technical lifecycle management.\nThe Director aligns the Advanced Analytics & Modeling Strategy with broader I&A priorities and partners with Analytics Strategy & Governance, and SPT leaders through explicit decision rights and connected portfolio governance.\nJob Description\nDirector, Advanced Analytics & Modeling\nLocation - Hyderabad #LI Hybrid\nMajor Accountabilities:\nAdvanced Analytics & Modeling Strategy & Capability Evolution\nDefine and continuously evolve the Advanced Analytics & Modeling (AAM) strategy, portfolio roadmap, capability maturity agenda, and investment priorities, ensuring alignment with portfolio priorities, launches, evolving customer and patient needs, and the broader I&A capability direction.\nEstablish and manage priorities across Precision Health, Key Drivers & Action Planning Analytics, Integrated Promotion Mix Modeling & Resource Optimization, and AI & Unstructured Intelligence, ensuring focus on the highest-value opportunities.\nGuide decisions on where advanced analytics capabilities should be built, incubated, partnered, scaled, automated, or retired based on business value, differentiation, feasibility, reuse potential, and maturity.\nPortfolio Prioritization, Capacity & Delivery\nEstablish transparent intake, prioritization, service levels, and portfolio governance across launch, brand, therapeutic-area, functional, and enterprise demand, ensuring Hyderabad capacity is allocated to the highest-value work with explicit trade-offs when demand exceeds capacity.\nBalance near-term decision support with sustained capability development, reusable methods, and cross-portfolio learning, while assigning one accountable analytical leader for cross-capability engagements to ensure integrated workplans, contributions, recommendations, and outcome measures.\nCapability Portfolio Leadership & Analytical Excellence\nEstablish shared expectations for analytical rigor, fit-for-purpose methods, validation, interpretability, reproducibility, documentation, peer challenge, privacy, compliance, and responsible AI across advanced analytics and modelling work.\nResolve priorities, dependencies, quality issues, and capability seams spanning predictive analytics, patient opportunity modeling, key drivers, causal measurement, IPMM, optimization, and emerging AI methods, while promoting reuse and consistency and preserving capability-specific technical standards with appropriate adaptation to business context.\nEmerging Capability: AI & Unstructured Intelligence\nEstablish the Advanced Analytics strategy, roadmap, use-case priorities, capability boundaries, and investment thesis for AI & Unstructured Intelligence, with a focus on high-value applications such as call-note and text analytics, NLP, GenAI, unstructured signal detection, evidence synthesis, summarization, and knowledge acceleration.\nDeploy AAM HYD expertise to test, learn, and build reusable analytical approaches while ensuring human oversight, interpretability, and responsible use.\nBusiness Partnership & Decision Impact\nTranslate strategic priorities into clear business questions and analytical agendas, challenging low-value, duplicative, or poorly framed demand.\nConvert analytical findings into implications, choices, recommendations, learning agendas, and measurable actions, advancing decision support through appropriate predictive, diagnostic, causal, experimental, optimization, and AI-enabled methods.\nIntegrated Partnership with SPT\nServe as the Advanced Analytics & Modeling (AAM) point of contact in AIDE/HYD to the SPT organization for initiatives requiring governed data, technical environments, reusable capabilities, productization, deployment support, ModelOps, or enterprise scale.\nEnsure AAM owns its strategy, portfolio, use-case framing, analytical requirements, fit-for-purpose methodology, ad hoc model development, validation, interpretation, recommendations, acceptance, and impact measurement, while partnering with the I&A EH leader and SPT to determine which use cases remain I&A-owned analytics versus those transitioning to SPT-owned products, recurring models, engines, or workflows.\nEnable portfolio-level ownership of feasibility, reuse, capacity, investment, dependencies, and lifecycle issues within the AAM remit, escalating broader enterprise issues through appropriate governance.\nGlobal US-Hyderabad Operating Model\nEstablish HYD as an integrated capability and delivery partner, engaged early in portfolio planning, business context, analytical design, execution, quality review, synthesis, and capability development.\nPartner with Hyderabad leadership to align capability roadmaps, capacity, expertise, decision rights, work ownership, quality expectations, documentation, and talent priorities, matching ownership to capability maturity, technical expertise, proximity needs, and business value rather than location-based handoffs.\nBuild HYD capability to independently lead repeatable and increasingly complex analytical work while maintaining shared accountability for quality, interpretation, and decision impact.\nMinimum Requirements\nEducation: Bachelor's degree in Statistics, Economics, Econometrics, Data Science, Applied Mathematics, Operations Research, Engineering, Computer Science, Life Sciences, Public Health, Business Analytics, or a related field required or Master's degree or doctorate in a relevant quantitative discipline preferred. \n12+ years of leadership experience in advanced analytics, data science, decision science, commercial analytics, healthcare analytics, or a related quantitative field. \nProven success defining and executing an Advanced Analytics strategy and capability roadmap across analytical domains. \nExperience leading senior capability owners, flexible expert teams, complex portfolios, and globally distributed analytics organizations. \nDemonstrated experience applying advanced analytics to consequential commercial, patient, healthcare, launch, or enterprise decisions. \nExperience establishing portfolio prioritization, capacity allocation, quality governance, and reusable capability models. \nStrong track record partnering with senior business and technology leaders and translating complex analytics into strategic choices and measurable action. \nExperience leading operating-model transformation, capability centralization or federation, and organizational change. \nLeadership skills\nLead and deploy HYD Associate Directors and high-performing teams across capability priorities, launches, therapeutic areas, and cross-portfolio initiatives, ensuring effective alignment of expertise to business needs.\nBuild strong talent and leadership depth by managing hiring, onboarding, objectives, coaching, performance, succession, career development, engagement, retention, rotations, communities of practice, and T-shaped skill development.\nFoster a culture of collaboration, constructive challenge, innovation, inclusion, continuous improvement, and accountability, while supporting I&A and AIDE leadership on talent priorities, capability planning, organizational operations, and site-level initiatives.\nSuccess Measurements\nPriority launch, brand, functional, and portfolio decisions are improved through timely, rigorous, and actionable Advanced Analytics, with Precision Health, Key Drivers, IPMM, and AI & Unstructured Intelligence delivering against clear roadmaps, quality standards, ownership boundaries, validated value, and measurable business outcomes.\nPortfolio priorities, capacity, and trade-offs are transparent, reducing low-value or duplicative work while reusable methods, assets, and quality practices improve consistency, speed, scalability, and cross-therapeutic-area learning.\nHYD, AAM, and SPT operate with clear ownership, effective deployment, timely lifecycle decisions, strong handoffs, growing capability, sustainable utilization, and shared value realization, reinforcing senior stakeholder confidence in analytical rigor, recommendations, role clarity, and decision impact.\nRequired Skills\nLeadership in Advanced Analytics & Modeling strategy, capability portfolio management, roadmap development, and investment prioritization.\nBroad fluency across predictive modelling, patient analytics, driver analytics, causal inference, experimentation, IPMM, ROI, response curves, optimization, NLP, GenAI, and unstructured analytics, with strong judgment on method fit, evidence quality, validation, interpretability, uncertainty, model risk, and responsible AI.\nStrong executive decision framing, business translation, stakeholder influence, conflict resolution, and portfolio trade-off management, with clear understanding of analytical versus technical ownership across analytics, modelling, products, platforms, and lifecycle management.\nPreferred Experience\nExperience in pharmaceutical, biotechnology, life sciences, healthcare, or another complex regulated industry, with exposure to product lifecycle, launches, customer and patient analytics, promotional investment, and healthcare delivery.\nExperience incubating emerging AI or unstructured-data capabilities, validating use cases before scale, and establishing integrated operating models with global capability centers and AI, data, product, or platform organizations.\nStrong healthcare and pharmaceutical commercial acumen across customer, patient, access, field, and investment decisions.\nExpertise in AI-enabled analytics, NLP, GenAI, unstructured-data methods, experimentation, simulation, and optimization, with familiarity in product management, agile delivery, analytical productization, ModelOps, and business-to-technology translation.\nStrong executive storytelling, strategic facilitation, organizational design, and transformation leadership skills.\nLocation: Hyderabad NKC | Hybrid | 3 days a week in office is mandatory.\nDirect Reports: 5 - 10 Direct Reportees\nTeam size: Team of 30+ Associates\nSkills Desired\nArtificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Stakeholder Engagement, Statistical Analysis, Time Series 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