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.
Requirements
- 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.
- Bachelorâs 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.