Pricing Data Scientist (Ref: 197980)
Job Description
Pricing Data Scientist
\n
Downers Grove, IL
\n
Hybrid Working (Tuesday – Thursday Onsite)
\n
Salary: Up to $100,000
\n
Contact: daniel.scott@forsythbarnes.com
\n
\n
Are you passionate about using data to solve real business problems?
\n
\n
We are partnering with a rapidly growing organization looking to add a Pricing Data Scientist to a high-impact Pricing & Analytics team. This role is ideal for someone who enjoys working with large datasets, building analytical solutions, and influencing commercial decisions through data-driven insights.
\n
\n
What You'll Be Doing
\n
\n
- \n
- Develop and enhance pricing models and pricing strategies.
- Analyze large datasets using SQL and Python.
- Build automated analytical processes and reporting solutions.
- Identify trends, opportunities, and risks through data analysis.
- Support forecasting, experimentation, and statistical modelling initiatives.
- Partner with business stakeholders to understand challenges and provide actionable recommendations.
- Present findings and insights to leadership teams.
- Contribute to the development of pricing and recommendation engines.
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
What We're Looking For
\n
\n
Essential:
\n
✅ 1–2 years of experience in Data Science, Analytics, Commercial Analytics, Revenue Analytics, or a related field
\n
✅ Strong Python skills
\n
✅ Strong SQL skills
\n
✅ Experience working with large datasets
\n
✅ Ability to explain technical findings to non-technical stakeholders
\n
✅ Strong problem-solving and analytical thinking
\n
\n
Preferred
\n
✅ Experience with Databricks or PySpark
\n
✅ Machine Learning and Statistical Modelling experience
\n
✅ Forecasting or Predictive Analytics experience
\n
✅ Power BI, Tableau, or dashboarding experience
\n
✅ Pricing, Revenue, Customer, or Commercial Analytics exposure
\n
\n
Why Apply?
\n
- \n
- Work directly with senior leadership.
- Join a fast-growing analytics function.
- Gain exposure to pricing strategy, forecasting, automation, and data science projects.
- Strong career progression opportunities.
- Collaborative team environment with significant investment in analytics and technology.
\n
\n
\n
\n
\n
\n
\n