REQ Solutions ยท 3 hours ago
Data Science Manager
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Responsibilities
Design and execute test measurement plans Collaborate with Channel Leads to develop A/B test designs to ensure clean read and sufficient sample size; pull audience lists as needed (e.g., number of test cells, duration, populations required for stat sig).
Make recommendations on the right testing approach (e.g., geo-split testing, conversion split testing).
Identify potential measurement risks for test ideas. Complete pre-test checks for audience randomization and test setup.
Write measurement plans and define primary and secondary KPIs for each test
Track and measure tests - share out results and impacts with key stakeholders.
Ensure tests are monitored with the appropriate cadence once live.
Conduct any interim reads of test results.
Discuss deep-dive hypotheses with test leads and measurement manager; run and provide insights from deep-dives.
Present preliminary results in working sessions; tell the story of the test.
Annualize impact at scale of A/B test results once aligned on scaled version of the test.
Advanced Statistical Modeling: Build and deploy advanced predictive models (e.g., propensity models, churn prediction, lead scoring) to optimize B2B marketing efforts and maximize ROI.
Reporting & Analytics: Develop and maintain dashboards, reports, and other data visualization tools to provide clear, concise, and actionable insights to senior leadership and cross-functional teams.
Have solid understanding of Google and Meta campaigns and digital platforms to pull campaign results and diagnosis campaign set up.
Data Infrastructure & Automation: Collaborate with data engineering and IT teams to ensure proper data infrastructure, integration, hygiene, and automation for marketing analytics workflows, ensuring data quality and accessibility.
Market & Customer Insights: Analyze market trends, customer behaviors, and competitor performance to identify new opportunities for marketing optimization and growth.
Strategic Collaboration: Work closely with the broader marketing and sales teams (including promotions, customer and product) to align on goals, refine strategies, and measure the effectiveness of campaigns and tactics.
Continuous Improvement: Stay up-to-date with the latest trends in data science, machine learning, and marketing analytics to continuously refine and enhance the company's data-driven marketing capabilities.
Team Leadership & Mentorship: Lead and mentor a digital marketing analyst, providing guidance on analytical best practices, statistical modeling techniques, and marketing-related data science methodologies.
Qualification
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Required
Minimum 5 years of experience in data science, statistical analysis, and marketing analytics
Proficient in statistical programming languages (Python, R) and data analysis tools (e.g., SQL, Excel)
Strong background in hypothesis testing, regression analysis, and experimental design (A/B testing)
Strong knowledge of data visualization tools (e.g., Tableau, Power BI, or similar)
Familiarity with CRM, marketing automation platforms (e.g., HubSpot, Marketo), and customer data platforms (CDPs)
Excellent project management and collaboration skills to work effectively with cross-functional teams
Understanding of B2B digital marketing principles and best practices
Knowledge of web analytics tools (e.g., Google Analytics)
Preferred
Experience with machine learning techniques, predictive modeling, and data mining
Excellent critical thinking and problem-solving skills with a focus on delivering actionable recommendations to drive business performance
Experience working with large-scale marketing data and integrating multiple data sources (e.g., CRM, digital marketing, third-party data)
Knowledge of marketing attribution models and multi-touch attribution analysis
Company
REQ Solutions
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Funding
Current Stage
Growth StageCompany data provided by crunchbase