Data Scientist – Marketing Analytics
Location: Remote USA
Contract Duration: 6 months (with potential extension to 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: 3+ 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 $100 – $125/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.