Senior Manager, Commercial Analytics & Business Intelligence

Description : 

The Senior Manager, Commercial Analytics & Business Intelligence, is a pivotal, hands-on leader within the Commercial Operations function as DBV-Technologies prepares for its first U.S. commercial launch in Peanut Allergy. Reporting to the Head of Commercial Operations & Analytics, this individual will help design and build the commercial analytics engine from the ground up - the dashboards, data pipelines, KPIs, and insights that turn a first-launch biotech into a decision-ready organization.

In a first-launch environment, analytics is not a back-office reporting function - it is a core strategic capability. Every targeting decision, segmentation model, incentive plan, and performance review depends on trustworthy data and sharp interpretation. This role sits at the intersection of business strategy, advanced analytics, and commercial execution, serving as a key partner to Marketing, Sales Leadership, Market Access, Forecasting, Finance, and Executive Leadership. The insights this individual produces will directly shape how the organization launches, learns, and refines its go-to-market model.

The ideal candidate pairs deep technical fluency - advanced SQL, strong Python, modern BI, and applied AI - with the business acumen and executive communication skills to influence senior stakeholders without formal authority. This is deliberately not a reporting-only profile: we are looking for a builder who is equally comfortable architecting a data model, engineering an automated pipeline, and standing in front of leadership to tell the story the numbers reveal.

Location: Warren, New Jersey - minimum 3 days on site

Salary Range : $150-180k

Key Responsibilities : 

Analytics, Reporting & Performance Management

• Design, build, and maintain commercial analytics, reporting, dashboards, KPIs, and performance-management processes that give leadership a real-time view of launch performance against plan.
• Develop KPI scorecards, trend analyses, and variance reporting for business performance reviews with senior leadership.
• Translate complex, multi-source analyses into clear, actionable recommendations for executive decision-making.

Data Sources & Commercial Insights

• Develop insights from pharmaceutical patient, prescriber, claims, specialty pharmacy, hub, and market access data sources, integrating disparate feeds into coherent business narratives.
• Build and maintain the analytical layer connecting Xponent, LAAD, claims, specialty pharmacy/hub, and payer data into usable, trustworthy assets.

Launch Planning, Targeting & Field Effectiveness

• Support launch planning through HCP-level targeting, segmentation, and call-plan analytics that focus field resources where they matter most.
• Provide incentive compensation (IC) analytics and field force effectiveness measurement, quantifying the relationship between promotional activity and downstream prescribing.
• Evaluate targeting and segmentation model performance post-launch and recommend refinements based on observed results.

Forecasting, Finance & Scenario Analysis

• Partner with Forecasting and Finance to evaluate business scenarios, performance drivers, and resource-allocation trade-offs.
• Provide analytical support that connects performance data to budget cycles, long-range planning, and executive reporting.

Data Governance & Best Practices

• Drive data governance, documentation standards, and analytical best practices so the organization’s data assets are reliable, compliant, and reusable.
• Build scalable, automated pipelines and reporting to reduce manual effort and increase speed and accuracy.

AI & Advanced Analytics

• Identify high-value AI use cases and translate them into measurable business outcomes, applying LLMs, generative and agentic AI, and automation to improve commercial processes and decision-making.
• Apply traditional machine learning and statistical methods (predictive modeling, segmentation, propensity) where they add commercial value.

Qualifications : 

Required

• 8-10 years of progressive experience in pharmaceutical analytics, commercial operations, business intelligence, or a closely related field.
• Advanced SQL proficiency, with the ability to write, optimize, and maintain complex queries against large commercial datasets.
• Strong Python skills for data engineering, automation, analytics, and predictive modeling.
• Hands-on experience with BI and visualization platforms such as Power BI, Tableau, or similar tools.
• Demonstrated experience with pharmaceutical commercial datasets, including IQVIA Xponent, IQVIA LAAD, claims data, specialty pharmacy and hub data, market access / payer data, and HCP-level targeting and segmentation datasets.
• Demonstrated success supporting pharmaceutical product launches, including targeting, segmentation, IC analytics, and field force effectiveness.
• Exceptional executive communication and storytelling skills, with a proven ability to influence cross-functional stakeholders without formal authority.
• Comfort operating in a fast-paced, ambiguous, prelaunch environment, balancing strategic thinking with hands-on execution.
• Bachelor’s degree required, preferably in a quantitative discipline (Statistics, Economics, Mathematics, Engineering, Life Sciences, or related field).

Preferred

• Experience supporting specialty, immunology, allergy, rare disease, or biologic product launches.
• Familiarity with cloud-based analytics environments and modern data architectures (e.g., AWS, Azure, Databricks, Snowflake).
• Experience applying AI within commercial pharmaceutical organizations - including LLMs, generative AI, agentic AI, and automation tooling.
• Experience with statistical analysis, predictive analytics, and data science methodologies.
• Experience within emerging biotech companies or resource-constrained, high-growth environments.
• Advanced degree (MBA, MS, or PhD) in a quantitative or business discipline.

Behavioral skills :  

• Curiosity: Keep on exploring uncharted territories. Always ask “why?” and more importantly “why not?”,

• Courage: Take smart risks, mentor each other to always do better & be accountable for our choices, our opinions, and our actions,

• Collaboration: Teamwork and spirit. Support each other and be equally involved in the achievement of our common goals,

• Credibility: Be transparent, follow through and build trust. Educate ourselves about our unique technology.