What are the responsibilities and job description for the Data Science Manager position at Blend?
Company Description
About Blend360: Blend360 is a premier AI services provider, committed to co-creating meaningful impact for our clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, we tackle significant challenges by seamlessly aligning human expertise with artificial intelligence. We are dedicated to unlocking value and fostering innovation for our clients by harnessing world-class talent and data-driven strategies. We believe that the power of people and AI can have a transformative impact on the world, creating more fulfilling work and innovative solutions for our people and clients.
Job Description
We are seeking a skilled and versatile Data Science Manager to join our growing team. In this role, you’ll collaborate with practice leaders, engineers, and cross-functional stakeholders to solve complex business challenges using data science and AI-driven approaches. You’ll work on end-to-end data science initiatives focused on marketing and sales optimization.
About Blend360: Blend360 is a premier AI services provider, committed to co-creating meaningful impact for our clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, we tackle significant challenges by seamlessly aligning human expertise with artificial intelligence. We are dedicated to unlocking value and fostering innovation for our clients by harnessing world-class talent and data-driven strategies. We believe that the power of people and AI can have a transformative impact on the world, creating more fulfilling work and innovative solutions for our people and clients.
Job Description
We are seeking a skilled and versatile Data Science Manager to join our growing team. In this role, you’ll collaborate with practice leaders, engineers, and cross-functional stakeholders to solve complex business challenges using data science and AI-driven approaches. You’ll work on end-to-end data science initiatives focused on marketing and sales optimization.
- Partner with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints.
- Translate business needs into actionable data science solutions, evaluating multiple approaches and clearly communicating trade-offs.
- Collaborate with stakeholders to define methodologies, deliverables, and project roadmaps.
- Leverage Machine Learning and Data Analysis to optimize marketing campaigns and sales initiatives.
- Design, manage and evaluate format experiments (eg. A/B tests, multi-factorial experiments, etc.) to improve campaign performance increasing engagement and conversion rates.
- Develop and manage detailed project plans including milestones, risks, owners, and contingency plans.
- 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.
- Build 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.
- Manage and mentor junior resource to support their growth and development, as well as overall team success.
- Present results to client stakeholders in plain business language.
- 5 years of hands-on experience in Data Science, including model building and ML Ops
- Extensive experience in email marketing, digital marketing, and call center analytics.
- Experience managing and mentoring junior people in multiple locations.
- Proficiency in Python, SQL, and Spark in Databricks.
- Familiarity with digital marketing ecosystem (e.g., clickstream analytics) and recommendation systems.
- Experience deploying models via APIs or integrating them into batch processing pipelines.
- Working knowledge of cloud platforms Azure experience preferred.
- Ability to manage data pipelines and ETL processes with a solid understanding of data engineering best practices.
- Strong communication and collaboration skills, including experience engaging directly with clients
- Familiarity with ML Ops tools such as ML Flow, Kubeflow, or SageMaker.
- Experience working in Agile environments with cross-functional teams.
- Familiar with Microsoft SQL Server ecosystem, including SSIS (SQL Server Integration Service).