Data Science Manager - MMM at Blend360

Columbia, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

08 Apr, 26

Salary

0.0

Posted On

08 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Marketing Mix Modeling, Advanced Analytics, Python, SQL, Excel, Business Communication, Storytelling, Problem Solving, Causal Inference, Experimentation, Predictive Modeling, Data Sourcing, Model Design, Model Validation, Data Manipulation, Data Extraction

Industry

Professional Services

Description

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com Job Description Blend360 is looking for a marketing data scientist with deep Marketing Mix Modeling (MMM) expertise to help drive high-impact, data-driven decisions for our client. In this role, you’ll own the end-to-end MMM process—from data sourcing and model development to translating complex analytics into clear, executive-level recommendations. You’ll work in a fast-paced, client-facing environment, partnering closely with stakeholders to solve ambiguous business problems through advanced analytics. What you’ll do: Lead end-to-end Marketing Mix Modeling (MMM), including model design, validation, and business recommendations Develop and validate advanced predictive and causal models (regression, time series, Lasso/Ridge, uplift) Design and analyze experiments such as A/B tests, geo-tests, synthetic control, and DiD Translate complex analytics into compelling stories and executive-ready presentations Collaborate with cross-functional teams and manage high-visibility deliverables under tight deadlines What you bring: Strong experience in marketing science, MMM, and advanced analytics Proficiency in Python, SQL, and Excel Ability to communicate clearly with technical and non-technical stakeholders A structured, detail-oriented approach to problem solving in fast-paced environments If you’re passionate about the intersection of data science and marketing—and want to work on impactful, high-visibility client work—we’d love to hear from you. Qualifications Marketing Mix Modeling (MMM) expertise: Deep understanding of the end-to-end MMM process, including data sourcing, model design and validation, and translating model outputs into clear, actionable business recommendations. Attention to detail under pressure: Proven ability to deliver complex, high-visibility work with accuracy and rigor while operating in fast-paced, deadline-driven environments. Business communication & storytelling: Strong capability to create polished executive-ready decks, simplify complex analytics, and confidently present insights to senior stakeholders. Problem-solving & advanced analytics mindset: Skilled at breaking down ambiguous business questions, deeply exploring data, and delivering actionable, insight-driven solutions. Technical proficiency: Python: Data manipulation, modeling, and automation SQL: Efficient data extraction and transformation Excel: Rapid analysis and data validation/sanity checks Machine Learning, Causal Inference & Experimentation: Build and validate predictive and causal models (e.g., regression, time series, uplift modeling, Lasso/Ridge) Design, execute, and analyze experiments, including geo-tests, A/B tests, synthetic control, and difference-in-differences (DiD) Additional Information All your information will be kept confidential according to EEO guidelines.

Responsibilities

Lead the end-to-end Marketing Mix Modeling (MMM) process, including model design, validation, and business recommendations. Collaborate with cross-functional teams to solve ambiguous business problems through advanced analytics.