Data Science Engineering Manager - (Remote - US)

Jobgether; United States; Remote; USD 155,000 - 215,000; Full time

Job summary

Join an innovative talent matching platform as a Data Science Engineering Manager, where you will lead a dynamic team in building scalable data infrastructure and machine learning systems. This role is perfect for hands-on leaders passionate about empowering technical teams to create impactful, data-driven products. Collaborate with cross-functional teams to operationalize models and ensure system performance, quality, and scalability. Enjoy a competitive salary, flexible work arrangements, and a supportive environment that encourages professional growth and work-life balance.

Benefits

Competitive salary

Annual bonus opportunities

Company-subsidized medical, dental, and vision plans

401(k) plan with employer match

Flexible PTO

Paid parental leave

Remote work flexibility

Wellness programs

Career development opportunities

Company-sponsored team events

Qualifications

• 3+ years managing engineering teams focused on data science or ML systems.
• 7+ years hands-on in backend, data, or ML engineering.

Responsibilities

• Lead and mentor a team of data science engineers for real-time data products.
• Oversee design and deployment of high-throughput data pipelines.

Skills

Python

SQL

Airflow

MLFlow

FastAPI

Docker

GCP

Machine Learning

Statistical Analysis

Education

Bachelor's in Computer Science

Master's or PhD preferred

Tools

BigQuery

Cloud Functions

Kubernetes

Job description

Data Science Engineering Manager - (Remote - US)

Data Science Engineering Manager - (Remote - US)

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About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Data Science Engineering Manager in the United States.

We're seeking a highly skilled and strategic Data Science Engineering Manager to lead the development of scalable data infrastructure, machine learning systems, and real-time analytics pipelines. In this role, you will guide a team of engineers working on production-grade data products that drive pricing models, personalization tools, and risk management systems. You'll collaborate closely with data scientists, engineers, and product teams to operationalize models and ensure system performance, quality, and scalability. Ideal candidates are hands-on leaders who thrive in fast-paced environments and are passionate about empowering technical teams to build high-impact, data-driven products.

Accountabilities:

• Lead and mentor a team of data science engineers to deliver robust, real-time data products
• Oversee the design and deployment of high-throughput data pipelines and MLOps infrastructure
• Collaborate with data science and engineering teams to operationalize and maintain ML models
• Ensure uptime, performance, and monitoring of data systems in production environments
• Contribute to architectural decisions around APIs, ML stacks, and cloud infrastructure
• Implement best practices in documentation, testing, deployment, and alerting
• Partner with stakeholders to align technical strategy with business objectives
• Champion the adoption of emerging technologies and practices across technical teams
  
  
  

Requirements

• 3+ years of experience managing engineering teams focused on data science or ML systems
• 7+ years of hands-on experience in backend, data, or ML engineering
• Proven track record of shipping and maintaining production data systems in cloud environments
• Deep knowledge of Python, SQL, and tools such as Airflow, MLFlow, FastAPI, and Docker
• Experience with GCP services (e.g., BigQuery, Cloud Functions, Kubernetes) and MLOps tools
• Familiarity with machine learning frameworks (e.g., PyTorch, scikit-learn, TensorFlow)
• Strong communication, cross-functional collaboration, and technical leadership skills
• Degree in Computer Science, Statistics, or related field; Master's or PhD preferred
• A background in simulation, personalization, or real-time ML is a strong plus
  
  
  

Benefits

• Competitive salary ranging from $155,000 to $215,000
• Annual bonus opportunities
• Company-subsidized medical, dental, and vision plans
• 401(k) plan with employer match
• Flexible PTO with a strong encouragement to take at least two weeks off
• 16 weeks of paid parental leave and additional paid disability benefits
• Modern work schedules and remote work flexibility
• Lifestyle enhancement and wellness programs
• Annual performance reviews and career development opportunities
• Company-sponsored team events and in-person gatherings
• Choice of Mac or Windows equipment provided
  
  
  

Jobgether hiring process disclaimer

This job is posted on behalf of one of our partner companies. If you choose to apply, your application will go through our AI-powered 3-step screening process, where we automatically select the 5 best candidates.

Our AI thoroughly analyzes every line of your CV and LinkedIn profile to assess your fit for the role, evaluating each experience in detail. When needed, our team may also conduct a manual review to ensure only the most relevant candidates are considered.

Our process is fair, unbiased, and based solely on qualifications and relevance to the job. Only the best-matching candidates will be selected for the next round.

If you are among the top 5 candidates, you will be notified within 7 days.

If you do not receive feedback after 7 days, it means you were not selected. However, if you wish, we may consider your profile for other similar opportunities that better match your experience.

Thank you for your interest!

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Non-profit Organizations and Primary and Secondary Education

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