100% Remote || Marketing Data Science Manager (with Media Mix Modeling exp.) || Mastek/UOPX || Remote (MST Time zone) || Contract

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Deepak Singh

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Mar 26, 2026, 12:24:00 PMMar 26
to Deepak Singh
Greetings,
Hope you are doing well!

We are looking for a Marketing Data Science Manager. Below is the job description for your reference. Please have a look and share the best level of your interest.

Role: Marketing Data Science Manager (with Media Mix Modeling exp.)

Client: Mastek
End Client: University of Phoenix (UOPX)
Location: 100% Remote (MST Time zone)
Type: Contract 

Job Description:
We are seeking a Marketing Data Science Manager who can bridge the gap between data modeling and business impact. This role will focus on leveraging data science models and analytical frameworks to generate actionable marketing insights, optimize campaign performance, and guide strategic decisions.
The ideal candidate combines strong analytical and technical skills with business acumen and communication ability to translate data into meaningful narratives for stakeholders.

Requirements
  • Education: Bachelor’s or Master’s degree in Statistics, Economics, Operation Research, Computer Science, Industrial Engineering, Mathematics, Marketing Analytics etc.
  • Analytical and technical skills:
    • Proficiency (10+ years) in analyzing complex data and models, derive and deliver actionable insights to provide data driven marketing strategy to stakeholders. Strong ability to translate model outputs into business insights and marketing recommendations.
    • Proficiency (7+ years) in statistical software such as SQL, R, Python, PBI for data wrangling and modeling.
    • Familiarity (5+ years) with AWS Sagemaker and Lambda functions. Terraform experience will be preferred.
    • Strong problem-solving skills and attention to detail.

Experience (required):
  • At least 10 years hands on experience in machine learning, marketing analytics, statistical modeling, marketing mix modeling.
  • At least 10 years experience with various statistical techniques such as regression analysis, time series analysis, and predictive modeling, optimization etc.
  • Familiarity (5+ years) with marketing research methodologies and tools.

Experience (good to have):
  • AI and multi-touch attribution model experience
  • Familiarity with ad platforms (Google Ads, DV360, etc.)
  • Experience in A/B testing or experimentation frameworks
  • Marketing Knowledge:
    • Deep understanding of marketing concepts, including advertising, distribution, and campaign strategies.
    • Familiarity with different marketing channels and their impact on business performance.
    • Knowledge of industry trends and best practices in marketing analytics.
  • Business Acumen:
    • Understanding of business objectives and how marketing analytics can support decision-making and drive business growth.
    • Ability to align marketing strategies with broader organizational goals and objectives.
  • Communication Skills:
    • Ability to communicate complex analytical findings to non-technical stakeholders in a clear and concise manner.
    • Collaborative approach to working with cross-functional teams, including media, creative, product, and finance.

Skills
  • Proficient in machine learning model and statistical model development, simulation and optimization and deployment in AWS
  • Proficient in SQL, Python, R for data integration and modeling projects
  • Advanced in AWS Sagemaker, EC2, S3, Terraform, Bitbucket, etc for deployment projects
  • Advanced in PBI, Excel, streamlit for analytics and visualization projects
  • Experience in Terraform, EC2, MMM, optimizer application will be a big plus

Key Responsibilities:
  • Develop and deploy predictive and statistical models to evaluate marketing performance (e.g., attribution, media mix modeling, churn, LTV, segmentation, optimization).
  • Partner with marketing, product team to translate modeling results into clear business insights & recommendations that drive growth and ROI and communicate implications to non-technical stakeholders.
  • Present findings to senior stakeholders through clear storytelling and visualization.
  • Visualize and present analytical results using tools like Power BI, Excel, etc.
  • Build and maintain scalable analytics pipelines using Python/R, SQL, and possibly cloud data platforms (GCP, AWS, Azure).
  • Partner with marketing operations to operationalize insights (e.g., audience targeting, spend optimization).
  • Collaborate with data engineers and analysts to improve data accessibility and accuracy.
  • Support ongoing model performance monitoring and iterative improvements.
  • Support MMM and app maintenance and development for simulation and optimization and further development. Push changes to production using AWS Sagemaker, EC2, Terraform, Bitbucket, etc.
  • Assist with ad-hoc data requests, data exploration and building business knowledge models. Build intelligent dashboards if needed using SQL, PBI.
  • Conduct cross-functional collaboration, stakeholder meetings and provide documentations and internal trainings.
  • Lead projects, manage timelines, and ensure deliverables meet the business objectives and are delivered on time.
  • Perform other duties as assigned or apparent.
  • Work with marketing and product teams to design experiments, measure campaign ROI, and inform strategy.
Key Discussion Points

1. Modeling & Technical Expectations

  • Candidates should demonstrate understanding of:

    • Statistical and forecasting models

    • Media Mix Modeling (MMM) – considered a strong plus

    • Optimization models

  • Hands-on modeling experience is important, though the role is not purely a developer role.

  • Core technical skills expected include:

    • Python / R

    • SQL

  • Strong statistical background combined with business acumen is preferred over purely technical depth.


2. Role Structure & Responsibilities

  • Role is an individual contributor, not a people manager.

  • No direct reports.

  • Strong collaboration expected with peer-level stakeholders, occasionally senior leadership.

  • Focus is on managing stakeholder expectations and managing/using models rather than managing people.
--
Regards,

Deepak Singh

Technical Team Lead

Email: Dsr.itr...@gmail.com

LinkedIn: www.linkedin.com/in/deepak-singh-rajput-8a7b6a21a/

221 River St 9th floor Hoboken, NJ 07030

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