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Mid Level Digital Marketing Data Scientist Jobs (NOW HIRING)

Mondo

Data Scientist

Manhattan, NY · On-site

$75 - $80/hr

Not eligible for visa sponsorship The client is seeking a mid-level Data Scientist to serve as the ... Partner with stakeholders across Retail, Digital, and Marketing to frame business questions and ...

Blink UX

Digital Content Specialist

New York, NY · Hybrid

$105K - $115K/yr

... looking for a mid-level Digital Content Specialist to help support client-facing digital ... marketing, finance, operations, computer science, engineering, or technology * Self-starter with ...

New

Blink UX

Digital Marketing Analyst

New York, NY · Hybrid

$105K - $115K/yr

... mid-level Digital Marketing Analyst to help support client-facing digital initiatives firm-wide ... If you would like more information about how your data is processed, please contact us. apply for ...

New

Leidos

Mid-Level Data Scientist

Springfield, VA · On-site

$73K - $132K/yr

Leidos is actively interviewing for a Mid-Level Data Scientist to join our team in Springfield, VA ... Experience in combining, digital cartography, computer, technology, GIS, cartographic and ...

Leidos

Mid-Level Data Scientist

Springfield, VA · On-site

$73K - $132K/yr

Leidos is actively interviewing for a Mid-Level Data Scientist to join our team in Springfield, VA ... Experience in combining, digital cartography, computer, technology, GIS, cartographic and ...

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Mid Level Digital Marketing Data Scientist information

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$37.5K

$122.7K

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How much do mid level digital marketing data scientist jobs pay per year?

As of Aug 6, 2026, the average yearly pay for mid level digital marketing data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a mid level digital marketing data scientist?

Mid Level Digital Marketing Data Scientists are professionals who analyze and interpret complex digital marketing data to help organizations make informed decisions. They use statistical methods, machine learning, and data visualization tools to uncover patterns in consumer behavior, campaign effectiveness, and market trends. Typically, they have a few years of experience and work closely with marketing teams to optimize strategies, improve targeting, and measure ROI. Their insights are critical for refining digital marketing efforts and achieving business goals.

What are some common challenges faced by mid level digital marketing data scientists, and how can they be addressed?

Mid-level digital marketing data scientists often encounter challenges such as integrating data from multiple sources, ensuring data quality, and translating complex analytics into actionable marketing insights for non-technical stakeholders. Addressing these challenges involves developing strong data cleaning and validation skills, becoming proficient in marketing analytics tools, and honing communication abilities to bridge the gap between technical analysis and marketing strategy. Collaborating closely with marketers, designers, and engineers can also help ensure that your insights align with business goals and drive impactful campaigns.

What is the difference between Mid Level Digital Marketing Data Scientist vs Digital Marketing Analyst?

AspectMid Level Digital Marketing Data ScientistDigital Marketing Analyst
Required SkillsData analysis, statistical modeling, marketing analytics, programming (Python, R)Data interpretation, reporting, basic analytics, Excel skills
Work EnvironmentCollaborates with data teams, marketing departments, uses advanced analytics toolsFocuses on campaign performance, reporting, and basic data tools
CertificationsGoogle Analytics, SQL, Python/R certifications often preferredGoogle Analytics, Excel certifications common

The Mid Level Digital Marketing Data Scientist typically handles complex data modeling and predictive analytics to optimize marketing strategies, requiring advanced technical skills. In contrast, a Digital Marketing Analyst focuses on interpreting data to assess campaign performance and generate reports. Both roles are essential in marketing teams but differ mainly in technical depth and analytical complexity.

What are the key skills and qualifications needed to thrive as a mid level digital marketing data scientist?

To thrive as a Mid Level Digital Marketing Data Scientist, you need a solid background in statistics, data analysis, and digital marketing concepts, usually backed by a degree in a quantitative field and relevant work experience. Familiarity with analytics tools like Google Analytics, SQL, Python, and data visualization platforms such as Tableau is typically required. Strong problem-solving, communication, and collaborative skills help you translate complex data into actionable marketing insights and strategies. These capabilities are essential to drive data-driven decision-making and optimize marketing performance in a competitive digital landscape.
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Mid Level Digital Marketing Data Scientist jobs near you
Infographic showing various Mid Level Digital Marketing Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Digital Marketing Data Scientist

Alten Calsoft Labs

Palo Alto, CA

Contractor

Re-posted 3 days ago

Job description

Company Description

ALTEN Calsoft Labs is an engineering and IT services company that innovates, integrates and transforms business leveraging digital technology.

Job Description

You will be a team member of the Digital Marketing Analytics team, working in the data sciences area, with specific focus on Digital Marketing business problems.

You'll be responsible for supporting analytics that drive business optimizations across the customer end-to-end journey. This role will support the full cycle of an experiment (from data-driven hypothesis generation to test design to analysis and interpretation) while also innovating on experimental methodologies that allow us to obtain meaningful results.

You should have hands-on technical experience in statistics, predictive modeling and other data sciences, as well as extensive experience in developing data-sets for data science projects. The position requires superb communication and advanced analytical skills.

 

Qualifications

         Total Indicative Experience: 4-7 Years (or equivalent education) with experience in Digital Marketing specifically.

         Hands-on experience with one or more of the primary data science tool-sets: R, SAS, SPSS, Python, and models such as ARIMA.

         Hands-on experience with Adobe Analytics, Tableau and/or Power BI.

         Experience using advanced analytics techniques to tackle digital marketing business problems, such as, pre-funnel behavior analysis to predict insights in the digital journey prior to web form conversions, insights across tactics, multi-touch attribution, campaign sequencing, ROI analysis for paid campaign efficacy, and forecasting for pipeline metrics.

         Working knowledge of methods such as regression, cohort analysis, hypothesis testing, cluster analysis with hands-on experience translating raw data from relational databases and Hadoop into modeling data sets (using Excel, SQL, SAS or other coding tools) is desired.

         Good business & technical communication skills, both verbal and written. Ability to explain and present analytics concepts to non-technical audiences. Ability to establish & cultivate relationships with all stakeholders.

         Proven project management and organizational skills. Ability to effectively prioritize time, manage expectations and deliverables. A self-starter, who proactively looks for new and better ways of doing things. Shows drive, passion and a sense of ownership.

         Graduate degree in data sciences, advanced analytics, statistics or related fields is preferred, or equivalent on-the-job experience (experience in high-tech enterprise business-to-business industry is ideal, as is prior experience from a reputed analytics firm doing similar work).

Additional Information

All your information will be kept confidential according to EEO guidelines.

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