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ProcDNA

Biopharma-focused commercial analytics and consulting

Marketing Mix Analytics Lead - Marketing Mix, Multi-Touch Attribution

Data ScienceConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 5 years of experience in Marketing Mix Modeling and marketing analytics.
  • Hands-on experience in Multi-Touch Attribution is mandatory.
  • Experience in commercial analytics, preferably within consulting or analytics organizations.
  • A strong foundation in regression, econometrics, statistical modeling, and marketing measurement techniques.
  • Proficiency in Python or R, along with SQL.
  • Experience working in client-facing roles.
  • Strong analytical and problem-solving skills.
  • Ability to translate complex analytical findings into clear business recommendations.
  • Strong communication and stakeholder management skills.
  • High ownership, collaboration, and delivery focus.

Responsibilities

  • Lead end-to-end Marketing Mix Modeling and Multi-Touch Attribution engagements, from problem structuring to final recommendations.
  • Analyze multi-channel marketing data to quantify channel effectiveness, contribution, attribution, and return on investment.
  • Apply statistical techniques such as regression modeling, adstock, saturation curves, and attribution methodologies.
  • Translate analytical outputs into actionable business insights and budget optimization strategies.
  • Develop client-facing presentations with clear storytelling and structured recommendations.
  • Collaborate with cross-functional teams to ensure high-quality delivery and alignment with business objectives.
  • Support the development of analytical tools and accelerator solutions for Marketing Mix Modeling, Multi-Touch Attribution, and reporting workflows.

Desired Qualifications

  • Pharmaceutical or life sciences domain experience; candidates with relevant Marketing Mix Modeling experience from other industries are also encouraged to apply.
  • Experience with advanced Marketing Mix Modeling techniques such as Bayesian modeling, time-series modeling, and other advanced marketing measurement methodologies.
  • Exposure to Generative AI-based Marketing Mix Analytics functionalities and AI-assisted analytics workflows.
  • Experience developing analytical tools, accelerators, or internal products for marketing analytics use cases.
  • Familiarity with measurement frameworks such as Test & Control, incrementality analysis, or causal inference.
  • Experience with modern data platforms such as Snowflake or Databricks, and visualization tools such as Power BI or Tableau.
  • Experience in consulting, analytics, or marketing effectiveness roles with hands-on exposure to Marketing Mix Modeling and Multi-Touch Attribution.
  • Pharmaceutical or life sciences industry experience; candidates from other domains with strong marketing measurement expertise will also be considered.

About the Company

ProcDNA

Biopharma-focused commercial analytics and consulting

ProcDNA focuses on commercial analytics and technology consulting for life sciences and biopharma. It helps clients turn data into actionable insights through analytics, technology, and data science services, including specialized offerings like Auxo HCP 360 for data management, marketing, and customer relationship optimization. The company delivers tailored solutions in areas such as commercial planning, market assessment, and patient journey quantification, enabling precise business decisions and growth. What sets ProcDNA apart is its deep expertise in market access analytics, sales strategy, and campaign ROI, backed by a leadership team with over a century of combined experience, a track record with 25 clients across 40 disease indications, and a presence in five office locations. The overarching goal is to drive growth for biopharma clients by turning complex data into clear, strategic actions.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
South San Francisco, CA
Founded
2019

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