Marketing Data Science Manager

Key Responsibilities

• Data Science & Analytics
• Partner with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints.
• Evaluate multiple approaches and clearly communicate trade-offs to translate business needs into actionable data science solutions.
• Collaborate with stakeholders to align on methodology, deliverables, and project roadmaps.
• Leverage Machine Learning and Data Analysis to optimize marketing campaigns.
• Conduct A/B tests to improve campaign performance, measure campaign effectiveness, and increase engagement and conversion rates.

AI & Generative AI

• Collaborate with AI and engineering teams to design and implement production-grade AI solutions leveraging LLMs, transformers, RAG, agentic workflows, and generative AI agents.
• Optimize prompt design, workflows, and pipelines for performance, accuracy, and cost-efficiency.
• Build multi-step, stateful agentic systems that utilize external APIs/tools and support robust reasoning.
• Deploy GenAI models and pipelines in production (API, batch, or streaming) with a focus on scalability and reliability.
• Create and maintain efficient data pipelines using SQL, Spark, and cloud-based big data technologies within client architectures.
• Collect, clean, and integrate large datasets from internal and external sources to support functional business requirements.
• Develop analytics tools that deliver insights across domains such as customer acquisition, operations, and performance metrics.
• Perform exploratory data analysis, data mining, and statistical modeling to uncover insights and inform strategic decisions.
• Train, validate, and tune predictive models using modern machine learning techniques and tools.
• Document model results in a clear, client-ready format and support model deployment within client environments.

Qualifications

• Required Skills & Experience:
• 5+ years of hands-on experience in Data Science, including model building and ML Ops.
• Experience in email marketing and direct marketing.
• Experience managing people.
• Proficiency in Python, SQL, and tools like Pandas, Scikit-learn, NLTK/spaCy, and Spark.
• Familiarity with digital marketing ecosystem (e.g., clickstream analytics) and recommendation systems.
• Working knowledge of cloud data platforms (e.g., AWS S3, Redshift, GCP, Azure).
• A strong understanding of data engineering best practices.
• Strong communication and collaboration skills, including experience engaging directly with clients.

• Preferred Qualifications:
• Exposure to ML Ops tools such as MLflow, Kubeflow, or SageMaker.
• Experience working in Agile environments with cross-functional teams.

Additional Information

The starting pay range for this role is $125,000 - $160,000. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. BLEND360 also offers a competitive benefits program to meet the health and financial well-being of our team and their families. You can look forward to a range of benefits including medical, dental, vision, 401K, PTO, paid holidays, commuter benefits, spending accounts, life insurance, disability coverage, and EAPs.