Sr. Manager, Data Scientist, Marketing Analytics

Jobgether SRL; United States; On-site; USD 136,000 - 176,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

401(k) matching

Paid time off

Career growth

Job summary

Jobgether SRL in the United States is seeking a Sr. Manager, Data Scientist, Marketing Analytics to lead a small team of data scientists and translate business priorities into data-driven strategies that improve campaign performance, customer insights, and ROI.

You will oversee modeling, experimentation, and optimization, partner with Marketing, Product, Sales, IT and Data Engineering, and shape the marketing analytics roadmap from development to production alongside senior leaders.

Qualifications

• Master’s or PhD in a quantitative field.
• 10+ years in data science with 2–3 years leading teams.
• Experience with ML, optimization, and large-scale data processing.
• Cross-functional collaboration and stakeholder influence.
• Experience with marketing analytics applications.
• Proficient Python and/or R; SQL skills.
• Big-data tech and cloud platforms.
• Strong communication and executive presence.
• Visa sponsorship not provided.

Responsibilities

• Lead and mentor a team of 2–3 data scientists.
• Oversee end-to-end data science projects from ideation to deployment.
• Develop marketing analytics roadmaps and models.
• Partner with Marketing, Product, Sales, IT, and Data Eng.
• Design A/B and multivariate tests for campaigns.
• Translate results into actionable executive recommendations.

Skills

Python

SQL

Machine learning

Cross-functional

Experiment design

Education

Advanced degree

Tools

Spark

Hadoop

AWS

GCP

Azure

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Manager, Data Scientist, Marketing Analytics based in the United States.

This senior leadership role will guide a team of data scientists in using advanced analytics to solve complex marketing and customer challenges.

You will translate business priorities into data-driven strategies that improve campaign performance, customer understanding, and return on investment.

The role combines people leadership with hands‑on oversight of statistical modeling, machine learning, experimentation, and optimization.

You will partner with Marketing, Product, Sales, IT, and Data Engineering leaders to identify high-value opportunities and deliver measurable business impact.

You will also shape the roadmap for marketing analytics and oversee models from initial development through production deployment and monitoring.

The position offers substantial visibility with senior leadership and requires the ability to turn sophisticated analytical findings into clear business recommendations.

This is a strategic, collaborative opportunity for an experienced data science leader who can connect technical innovation with real‑world marketing outcomes.

Accountabilities

• Lead, mentor, and develop a team of 2–3 data scientists, establishing clear objectives, providing feedback, conducting performance reviews, and supporting professional development.
• Foster a collaborative, high‑performing environment while managing competing priorities across multiple data science initiatives.
• Oversee the full lifecycle of data science projects, from ideation and prototyping through deployment, production monitoring, and optimization.
• Review statistical and optimization models to ensure technical rigor, business relevance, data integrity, and adherence to appropriate ethical standards.
• Partner with Marketing leadership and business stakeholders to understand strategic objectives and identify opportunities where data science can create measurable value.
• Define and execute the marketing analytics roadmap in alignment with broader business priorities.
• Lead the development and implementation of advanced analytical models, including attribution, customer lifetime value, segmentation, propensity, personalization, and media mix modeling.
• Design and oversee A/B and multivariate testing frameworks to measure the impact of marketing initiatives.
• Apply statistical modeling, machine learning, optimization techniques, and experimental design to address complex marketing challenges.
• Ensure data collection, preparation, feature engineering, model development, validation, deployment, and monitoring are executed effectively.
• Collaborate with data engineering teams to develop scalable data pipelines and analytical infrastructure.
• Contribute hands‑on expertise to deploying machine learning models within modern data science environments.
• Champion emerging data science methods and technologies that can improve marketing performance and customer insights.
• Translate complex analytical results into clear, actionable recommendations for marketing teams and senior executives.
• Serve as a subject matter expert in data science and marketing analytics across the organization.
• Collaborate with Marketing, Product, Sales, IT, and Data Engineering to drive cross‑functional initiatives.
• Stay current with industry trends, emerging technologies, and evolving best practices in marketing analytics and data science.

Requirements

• Master’s or PhD in Data Science, Operations Research, Applied Mathematics, Computer Science, or a related quantitative field.
• 10+ years of progressive experience in data science, including at least 2–3 years leading or managing data science teams.
• Extensive experience with machine learning, predictive analytics, optimization algorithms, and large‑scale data processing.
• Demonstrated experience working cross‑functionally and influencing stakeholders at multiple organizational levels.
• Experience with several marketing analytics applications, such as demand forecasting, customer segmentation, experimentation, predictive customer response, price optimization, marketing mix modeling, customer journey analytics, next‑best‑product/offer modeling, or customer elasticity analysis.
• Expert‑level proficiency in Python, including tools such as NumPy, pandas, scikit‑learn, TensorFlow, or PyTorch, and/or strong proficiency in R.
• Strong SQL skills for data extraction, transformation, and analysis.
• Experience with big‑data technologies such as Spark or Hadoop and cloud platforms such as AWS, GCP, or Azure.
• Strong understanding of statistical inference, experimental design, and causal analysis.
• Proven ability to build, deploy, monitor, and maintain machine learning models in production environments.
• Experience developing scalable analytical pipelines and working with modern data science technology stacks.
• Excellent written, verbal, presentation, and interpersonal communication skills.
• Executive presence and ability to explain complex technical concepts clearly to both technical and non‑technical audiences.
• Strong strategic thinking, problem‑solving capabilities, and business judgment.
• Ability to manage multiple priorities while maintaining high standards for quality and delivery.
• Willingness to collaborate across a large, geographically distributed organization.
• Employment does not include visa sponsorship or OPT support.

Benefits

• Annual base salary range of $135,700–$176,400, with actual compensation potentially varying based on geographic location, skills, education, and experience.
• Potential additional earnings through applicable incentives and performance‑based compensation.
• Full‑time colleagues receive benefits beginning on their first day of employment, with no waiting period.
• Medical, dental, and vision insurance.
• Disability and life insurance coverage.
• 401(k) retirement plan with company matching contributions.
• Vacation and sick days.
• Company‑paid holidays and floating holidays.
• Tuition reimbursement for eligible full‑time employees.
• Training and professional development programs.
• Multiple opportunities for career growth and advancement.
• Flexible work environment with an emphasis on health, safety, and work‑life balance.
• Opportunity to lead a specialized data science team and influence enterprise‑level marketing strategy.