Marketing Data Scientist, Measurement & Modeling

HDJ & Associates, Inc.; Pittsburgh (Allegheny County); On-site; USD 120,000 - 160,000; Full time

Job summary

HDJ & Associates, Inc. is seeking a marketing data scientist to shape strategy through advanced analytics, ML, experimentation, and AI-enabled tools.

The role connects digital engagement with offline outcomes across our national network, focusing on measurement and analytical decision support rather than day-to-day media buying. You will partner with marketing and e-commerce teams to design experiments, build predictive models, and translate insights into actionable business recommendations,

Qualifications

• 3 years of relevant professional experience applying advanced analytics or data science to business problems with measurable impact.
• Strong knowledge of statistical methods, hypothesis testing, regression analysis, causal inference, forecasting, and experimental design.
• Hands-on experience with large, complex datasets and building predictive models in cloud or distributed computing environments.
• Proficiency in Python and SQL for data analysis, modeling, and workflow development.
• Experience with cloud-hosted data platforms such as Google Cloud Platform, AWS, or similar environments.
• Familiarity with marketing analytics, customer behavior analysis, campaign measurement, customer segmentation, and customer lifecycle concepts.
• Comfort collaborating with IT on tracking and data pipelines, including server-side tracking, conversion APIs, and Online-to-Offline measurement.
• Experience translating ambiguous business questions into structured analytical plans and practical solutions.
• Proven ability to learn quickly and leverage emerging marketing technologies, particularly AI-based measurement and optimization models.
• Strong communication skills, with the ability to work cross-functionally and explain technical concepts to business stakeholders.

Responsibilities

• Experimentation & Measurement: Lead test design and analysis, including A/B testing, market selection, incrementally testing, media mix modeling, holdout design, and final readouts to measure business impact.
• Business Partnership: Collaborate closely with marketing, ecommerce, and other digital business stakeholders to solve problems, identify opportunities, and drive data-informed decisions.
• Reporting and Analytics: Establish and maintain reporting and performance review KPIs such as ROAS, CPA, LTV, unit economics and contribution metrics across both customer acquisition and retention.
• Data & Platform Integration: Partner with IT teams to define data requirements, validate data quality, and enable reliable datasets from GA4/BigQuery and advertising platforms for analysis, measurement, and decision-making.
• Predictive & Analytical Modeling: Develop and adapt predictive, statistical, and optimization models to support initiatives across customer acquisition, activation, engagement, retention, promotion planning, and channel performance.
• AI & Advanced Analytics: Apply modern AI and machine learning techniques, including LLM and generative AI tools where appropriate, to improve analysis, workflow efficiency, insight generation, and decision support.

Skills

Python

SQL

Cloud platforms

Experimentation

Statistics

Communication

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Economics, OR related field

Tools

GA4/BigQuery

AWS

Job description

Our client is seeking a highly analytical, curious, and results-driven marketing data scientist to join our marketing team. In this role, you will help shape marketing and commercial strategy through advanced analytics, machine learning, experimentation, and modern AI-enabled tools. A critical focus of this position is solving the \"Online-to-Offline\" puzzle by developing sophisticated models to connect digital engagement with physical outcomes across our national network of retail branches and service centers.

You will work across a wide range of initiatives, including customer acquisition, retention, segmentation, promotion optimization, forecasting, and marketing effectiveness. The ideal candidate brings strong statistical and technical skills, a practical business mindset, and the ability to translate complex data into actionable recommendations. This role will also help advance use of modern data science capabilities, including cloud-based modeling, ML workflows, generative AI tools, and privacy-aware measurement.

This role focuses on measurement, experimentation, and analytical decision partnership rather than day-to-day media buying or primary ownership of marketing-platform administration.

• Experimentation & Measurement: Lead test design and analysis, including A/B testing, market selection, incrementally testing, media mix modeling, holdout design, and final readouts to measure business impact.

• Business Partnership: Collaborate closely with marketing, ecommerce, and other digital business stakeholders to solve problems, identify opportunities, and drive data-informed decisions.

• Reporting and Analytics: Establish and maintain reporting and performance review KPIs such as ROAS, CPA, LTV, unit economics and contribution metrics across both customer acquisition and retention.

• Data & Platform Integration: Partner with IT teams to define data requirements, validate data quality, and enable reliable datasets from GA4/BigQuery and advertising platforms for analysis, measurement, and decision-making.

• Predictive & Analytical Modeling: Develop and adapt predictive, statistical, and optimization models to support initiatives across customer acquisition, activation, engagement, retention, promotion planning, and channel performance.

• AI & Advanced Analytics: Apply modern AI and machine learning techniques, including LLM and generative AI tools where appropriate, to improve analysis, workflow efficiency, insight generation, and decision support.

• Data Science Execution: Execute end-to-end projects by scoping business objectives, designing analytical approaches, building models, validating results, and delivering measurable solutions.

• Insight Communication: Communicate findings clearly through visualizations, presentations, and written summaries, translating complex analyses into practical business recommendations.

• 3 years of relevant professional experience applying advanced analytics or data science to business problems with measurable impact.

• Strong knowledge of statistical methods, hypothesis testing, regression analysis, causal inference, forecasting, and experimental design.

• Demonstrated ability to independently scope, prioritize, and deliver analytical work with limited day-to-day technical oversight.

• Hands-on experience working with large, complex datasets and building predictive models in cloud or distributed computing environments.

• Proficiency in Python and SQL for data analysis, modeling, and workflow development.

• Experience with cloud-hosted data platforms such as Google Cloud Platform, AWS, or similar environments.

• Familiarity with marketing analytics, customer behavior analysis, campaign measurement, customer segmentation, and customer lifecycle concepts.

• Comfort collaborating with IT on tracking and data pipelines, including server-side tracking, conversion APIs, and Online-to-Offline measurement.

• Experience translating ambiguous business questions into structured analytical plans and practical solutions.

• Proven ability to learn quickly and leverage emerging marketing technologies, particularly AI-based measurement and optimization models.

• Strong communication skills, with the ability to work cross-functionally and explain technical concepts to business stakeholders.

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Economics, Operations Research, or a related field; advanced degree preferred.

PREFERRED QUALIFICATIONS

• Experience supporting ecommerce, retail, distribution, or other customer-focused commercial organizations.
• Experience with marketing measurement, attribution, incrementally testing, media optimization, or promotion analytics.
• Experience measuring marketing impact across both digital and offline outcomes, including branch visits, phone calls, and offline revenue.
• Experience building reusable analytical workflows and collaborating IT to operationalize high-value outputs.
• Familiarity with web tracking, digital analytics, and modern measurement frameworks such as GA4, conversion APIs, or privacy-aware analytics environments.
• Experience with AI tools and/or machine learning systems in real-world business settings.
• Knowledge of data visualization and BI platforms such as Power BI, Looker, or similar tools.