The
Senior Manager/Head - Sales Analytics
, serves as a strategic analytics partner to field sales leadership. This role is responsible for delivering sub-national insights and performance analytics that drive data-informed decision making, optimize resource allocation, and enhance field force effectiveness. The Head will collaborate closely with Commercial and Marketing teams to ensure alignment on methodologies and a unified view of performance across geographies. This role is critical in translating data into actionable strategies that enable sales teams to execute with precision and maximize impact in the field. This position will report to the Head – Commercial Excellence and will be based in Bangalore.
Main Responsibilities:
Strategic partner to Field Sales leadership
within a designated Therapeutic Area, supporting territory- and region-level planning, opportunity analysis, performance reviews, resource optimization, and new indication launches with actionable, sub-national analytics.
Single point of contact for Customer Facing Capabilities for the Field
– Triage and manage multiple questions around Field Effectiveness
Develop, track, and refine KPIs
that measure field sales execution and effectiveness, ensuring alignment with national brand strategy supporting marketing teams.
Co-Lead the creation and delivery of sub-national performance insights
, translating data into strategic recommendations that inform field resource allocation, incentive design, pull-through strategies, and performance optimization.
Co-lead ad-hoc and recurring sub-national analyses
, identifying trends and opportunities across geographies and customer segments using metrics such as call activity, HCP engagement, territory coverage, and pull-through effectiveness.
Develop and manage field-facing dashboards and reporting tools
that synthesize key sales metrics and enable real-time decision-making for field leaders and senior commercial stakeholders.
Liaise with external vendors and internal partners
to ensure delivery of high-quality, timely sub-national Sales Force Effectiveness (SFE) reports that are fit-for-purpose and actionable.
Co-lead and Field Collaborate in the design and measurement of field tactics
, including targeting effectiveness, sales cadence, pull-through initiatives, and deployment optimization strategies.
Ensure data integrity and reliability
by working closely with data governance and commercial data management teams to validate sources, define metrics, and troubleshoot inconsistencies.
Mentor junior analysts or matrixed team members
by sharing therapeutic-area-specific knowledge, analytics best practices, and business acumen to drive team effectiveness and career growth.
BASIC
QUALIFICATIONS:
BA / BS with a minimum of 7-years of experience in pharmaceutical Analytics, Forecasting, and / or Sales Operations; equivalent combination of education (MS / MA / MBA) and / or consulting experience may be considered
Proven business acumen, with strong communication & presentation skills
Well-developed strategic thinking ability, with capacity to synthesize disparate sources of data to provide a coherent narrative and actionable insights
Strong analytical skills, with ability to design, develop, and execute analyses to answer complex business questions
Life sciences analytics experience, with understanding of best practices and ability to access and manipulate large data sets via cloud-based data warehouse / analytics platforms
Experience with key pharmaceutical data sources and analytics platforms, including:
National-level sales / demand data (e.g., IQVIA, Mckinsy etc.,)
CRM systems (e.g., Veeva, Salesforce, etc.)
Data management & analysis platforms
Data visualization / business intelligence tools (e.g., Power BI, Tableau, Qlik, etc.)
MS Office applications (Excel, PowerPoint, Word)
Excellent project management and prioritization skills, able to deftly balance multiple projects / priorities
Ability to work in a matrixed environment with many cross-functional partners to understand and influence key business decisions
PREFERRED
QUALIFICATIONS:
Ability to thrive in a fast-paced environment, comfortable with ambiguity, and with a track record of delivering exceptional results
Experience with programming languages (e.g., SQL, R, Python, etc.) and data science principles
Experience in applying AI / Machine Learning / data science methodologies to address complex quantitative questions and derive actionable insights
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