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Director Data Science

Location : Remote US
Job Type : Permanent @ BLEND360
Reference Code : 27489738
Hours : Full Time
Required Years of Experience : 5
Required Education : Master's Degree
Travel : Yes
Relocation : No
Job Industry : Consulting
Job Category : Data Science

Job Description :


Dynamic, Fast-growing, Entrepreneurial Data Science Solutions Company seeking seasoned Data Scientists! If you’ve got entrepreneurial spirit and passion, are driven by results, and want to be a part of significant growth, we’re looking for you! 

BLEND360 is an award-winning, new breed Data Science Solutions Company focused on powering exceptional results to our Fortune 500 clients. We are a growing company—born at the intersection of advanced analytics, data and technology.  

BLEND360 it is all about advancing our clients marketing capabilities and performance. If you are ready to embrace the challenge and would like to join our team as one of our Data Scientists, please keep reading!


As Data Scientists, we work with business leaders to solve clients’ business challenges and improve clients’ marketing results. We contribute our Advanced Data Science subject matter expertise to the recommendations and solutions delivered to our clients. We spend the majority of our time on getting data into proper shape, performing statistical analyses, developing predictive models and machine learning algorithms to solve clients’ business problems. 

We evaluate different sources of data, discover patterns hidden within raw data, create  insightful variables, and develop competing models with different machine learning algorithms. We validate and cross validate our recommendations to make sure our recommendations will perform well over time.


Our Directors of Data Science :

  • Provide leadership for digital marketing projects, including data source evaluation, predictive model development, campaign execution, marketing campaign reporting, and campaign dashboard creation. 

  • Manage project work and overall performance of data scientists, marketing analysts, and business intelligence analysts, including hiring and training new employees and making personnel decisions. 

  • Analyze team key performance indicators and develop solutions to achieve marketing goals.

  • Contribute to thought leadership in predictive modeling and model development through original research and presentations. 

  • Own client digital marketing projects, including defining project requirements and budgets with client, assigning and overseeing work and setting deadlines, creating comprehensive project plans, and measuring performance and performing risk assessments. 

  • Provide strategic assistance in developing project scope and objectives, and in allocating resources. 

  • Build positive client relationships by understanding client needs, holding regular meetings, and communicating directly with clients. 

  • Use data science software languages to construct and employ scalable statistical and mathematical models to be used across data analyses, including customer look-a-like models, campaign response models, incremental models, customer segmentation models, and customer lifetime value models. 

  • Deliver various qualitative and quantitative analysis tasks, such as defining predictive model development processes; querying modeling datasets using SQL; conducting data imputation, feature engineering, and variable selection; developing and tuning models using R or Python; and deploying models using SQL

  • Could be travel to clients



Required Qualifications :


  • Master’s degree in data science, marketing analytics, statistics, math, economics, or a related fields.

  • Five or more years of related professional experience, including three years of experience with each of the following: an advanced data science software language (such as Python, R, or SQL); cloud-based platforms (such as AWS, Azure, or Google); Adobe Marketing Cloud, Google Analytics, or Salesforce Marketing Cloud; web tagging, including Adobe DTM/Launch or Google Tag Manager; advanced Excel features; and statistical theory and modeling.


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