Data Scientist - Marketing

Data Scientist – Marketing

Location:   Remote USA

Contract Duration:  9 months

Contract Type:   W2 through Staffing Supplier

Position Overview: 

Our client’s Marketing Data Science & Analytics team is seeking a Data Scientist Contractor to drive operational efficiency, optimize campaign strategy, and enhance tooling infrastructure. This role combines tactical problem-solving with strategic influence, offering the opportunity to shape data-driven decisions that impact marketing performance at scale. 

Key Responsibilities: 

• Campaign Analysis & Strategy: Analyze campaign performance data to identify trends, inefficiencies, and growth opportunities. Translate insights into actionable recommendations to refine targeting and budget allocation 
• Operational Process Optimization: Diagnose bottlenecks in marketing workflows (e.g., reporting) and design scalable solutions (e.g., automation programs, dashboards). 
• Tooling Infrastructure Development: Build and refine tools to streamline data pipelines, reporting systems, and cross-functional collaboration (e.g., SQL, BI tools, workflow orchestration). 
• Cross-functional Collaboration: Partner with Marketing, Engineering, and Product teams to align technical solutions with business objectives. 
• Insights-to-Action: Transform raw data into strategic narratives that inform marketing decisions and operational improvements. 

Qualifications: 

• Technical Expertise: Proficiency in SQL, and data visualization tools (e.g., Tableau, Looker). 
• Analytical Mindset: Strong problem-solving skills with a track record of optimizing processes, tooling, or campaign strategies. 
• Communication: Ability to distill complex data insights into clear, actionable recommendations for non-technical stakeholders.
• Experience: 2+ years in data science, analytics, or a related field. Prior work in marketing analytics or operations is a plus.

A reasonable estimate of the compensation range for this position is $75 – $85/hr. The compensation range is specific to the United States and incorporates many factors including but not limited to an applicant’s skills and prior relevant experience and training; licensures, degrees, and certifications; internal equity; internal pay ranges; and market data/range parameters.