Translate client business questions into scoped data science problems and success measures
Design and oversee ML solutions across the pharma commercial lifecycle
Own client communication and provide thought leadership on business decisions
Lead project delivery across timelines, scope and team allocation
Mentor and manage a team of data scientists
From the employer’s posting
Work with clients to translate business questions into well-scoped data science problems
Design and oversee ML solutions across the pharma commercial lifecycle
Own client communication and relationships and provide thought leadership to support their business decisions.
Lead project delivery across timelines, scope and team allocation
Mentor and manage a team of data scientists
Education & alternatives
- 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.
- A Bachelor's or Master's degree in engineering, statistics, mathematics or a relevant quantitative field.
- Experience with life sciences data, such as claims (Komodo, IQVIA, Symphony), specialty pharmacy, CRM, DDD, Lab and other HCP, account or patient-level data.
About ProcDNA
We fuse design thinking with cutting-edge tech to create game-changing Commercial Analytics and Technology solutions for our clients.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
SQL
AWS
Azure
Databricks
PySpark
Where the posting names them
- Strong depth in Statistics, supervised and unsupervised ML, Deep learning and GenAI concepts, along with experience in deploying models to production.
- Strong Python and SQL, with experience on distributed or cloud platforms such as Databricks, PySpark and AWS/Azure.
- A track record of owning client communication and explaining results to non-technical stakeholders.
New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
ProcDNA 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?
What are we looking for
We 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.
What you'll do:
Work with clients to translate business questions into well-scoped data science problems, and define the approach, data requirements and success measures.
Design and oversee ML solutions across the pharma commercial lifecycle, and choose methods that fit the data and the decision they support.
Own client communication and relationships and provide thought leadership to support their business decisions.
Quality-check the team's work and guide models to production through cross-team collaboration.
Lead project delivery across timelines, scope and team allocation, often across parallel engagements.
Mentor and manage a team of data scientists, and keep yourself and the team current with advancements in the field for collective growth.
Contribute to business development and internal capability building through proposals, POCs and reusable offerings, and help the practice grow
Must have:
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.
A Bachelor's or Master's degree in engineering, statistics, mathematics or a relevant quantitative field.
Experience with life sciences data, such as claims (Komodo, IQVIA, Symphony), specialty pharmacy, CRM, DDD, Lab and other HCP, account or patient-level data.
Strong depth in Statistics, supervised and unsupervised ML, Deep learning and GenAI concepts, along with experience in deploying models to production.
Strong Python and SQL, with experience on distributed or cloud platforms such as Databricks, PySpark and AWS/Azure.
A track record of owning client communication and explaining results to non-technical stakeholders.
Experience in guiding and managing a team of data scientists.