Mid Level Data Manager Jobs
Mid level data manager jobs go to professionals ready to own data pipelines end to end, mentor junior analysts, and drive governance decisions with limited oversight. Roles are split across on-site, remote, and hybrid settings in Technology & Software, Consulting & Professional Services, and Retail, with employers like Amazon, Apple, and Speechify hiring at this level now.
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About ABC Legal Services
ABC Legal Services is the nation's premier process serving and court filing company, operating across all 50 states. We are a technology-forward legal services company on a mission to make legal processes faster, smarter, and more reliable. Our data and engineering teams are central to that mission — building models and systems that power operations at scale. We're now looking for a Data Scientist with strong ML engineering and MLOps experience to help us take our machine learning capabilities to the next level.
Role Overview
We're seeking a Data Scientist with hands-on experience in machine learning engineering and MLOps. In this role, you'll own the full model lifecycle — from research and experimentation through deployment, monitoring, and iteration. You'll work within our AWS SageMaker Studio environment and collaborate closely with engineering, operations, and product teams to deliver models that drive measurable business outcomes.
Key Responsibilities
- Develop, train, and evaluate machine learning models to solve business problems across operations, legal services, and marketing
- Own the full ML lifecycle: data preparation, feature engineering, model training, validation, deployment, and monitoring
- Build and maintain MLOps pipelines using AWS SageMaker Studio, including experiment tracking, model registry, and automated retraining workflows
- Partner with product and operations teams to translate business requirements into data science solutions
- Monitor deployed models in production, identify performance degradation, and drive continuous improvement
- Document methodologies, model performance benchmarks, and technical decisions for internal knowledge sharing
- Stay current with advances in ML and data science tooling, and advocate for best practices across the team
Requirements
Required
- 3+ years of experience in data science or a closely related role, with demonstrated ML engineering and MLOps responsibilities
- Strong proficiency in Python for data science and ML development (pandas, scikit-learn, PyTorch or TensorFlow)
- Hands-on experience with AWS SageMaker Studio for model development, training, and deployment
- Solid understanding of MLOps principles: model versioning, pipeline automation, drift detection, and production monitoring
- Experience with SQL and working with structured data in cloud data warehouses or relational databases
- Proven ability to translate complex data science findings into clear, actionable insights for non-technical stakeholders
- Strong self-direction and communication skills suited for a remote work environment
Nice to Have
- Experience in the legal, collections, or financial services industry
- Background in targeted mail marketing, direct mail modeling, or customer segmentation
- Familiarity with AI coding agents and agentic development workflows (e.g., Claude, Copilot, Cursor, or similar tools)
- Experience with propensity modeling, uplift modeling, or response prediction
- Exposure to LLM-based workflows or applied NLP in a production setting
- Data engineering experience with modern tooling such as Dagster, Airbyte, and dbt
- Familiarity with AWS data services including Glue, Lambda, Redshift, and Step Functions
Compensation & Benefits
- Fully remote position with flexible working hours
- Comprehensive health, dental, and vision insurance
- 401(k) with company match
- Paid time off and company holidays
- Opportunity to shape data science strategy at a growing, industry-leading company
Salary Range: $110,000-$130,000 depending on experience
About ABC Legal Services
ABC Legal Services is the nation's premier process serving and court filing company, operating across all 50 states. We are a technology-forward legal services company on a mission to make legal processes faster, smarter, and more reliable. Our data and engineering teams are central to that mission — building models and systems that power operations at scale. We're now looking for a Data Scientist with strong ML engineering and MLOps experience to help us take our machine learning capabilities to the next level.
Role Overview
We're seeking a Data Scientist with hands-on experience in machine learning engineering and MLOps. In this role, you'll own the full model lifecycle — from research and experimentation through deployment, monitoring, and iteration. You'll work within our AWS SageMaker Studio environment and collaborate closely with engineering, operations, and product teams to deliver models that drive measurable business outcomes.
Key Responsibilities
- Develop, train, and evaluate machine learning models to solve business problems across operations, legal services, and marketing
- Own the full ML lifecycle: data preparation, feature engineering, model training, validation, deployment, and monitoring
- Build and maintain MLOps pipelines using AWS SageMaker Studio, including experiment tracking, model registry, and automated retraining workflows
- Partner with product and operations teams to translate business requirements into data science solutions
- Monitor deployed models in production, identify performance degradation, and drive continuous improvement
- Document methodologies, model performance benchmarks, and technical decisions for internal knowledge sharing
- Stay current with advances in ML and data science tooling, and advocate for best practices across the team
Requirements
Required
- 3+ years of experience in data science or a closely related role, with demonstrated ML engineering and MLOps responsibilities
- Strong proficiency in Python for data science and ML development (pandas, scikit-learn, PyTorch or TensorFlow)
- Hands-on experience with AWS SageMaker Studio for model development, training, and deployment
- Solid understanding of MLOps principles: model versioning, pipeline automation, drift detection, and production monitoring
- Experience with SQL and working with structured data in cloud data warehouses or relational databases
- Proven ability to translate complex data science findings into clear, actionable insights for non-technical stakeholders
- Strong self-direction and communication skills suited for a remote work environment
Nice to Have
- Experience in the legal, collections, or financial services industry
- Background in targeted mail marketing, direct mail modeling, or customer segmentation
- Familiarity with AI coding agents and agentic development workflows (e.g., Claude, Copilot, Cursor, or similar tools)
- Experience with propensity modeling, uplift modeling, or response prediction
- Exposure to LLM-based workflows or applied NLP in a production setting
- Data engineering experience with modern tooling such as Dagster, Airbyte, and dbt
- Familiarity with AWS data services including Glue, Lambda, Redshift, and Step Functions
Compensation & Benefits
- Fully remote position with flexible working hours
- Comprehensive health, dental, and vision insurance
- 401(k) with company match
- Paid time off and company holidays
- Opportunity to shape data science strategy at a growing, industry-leading company
Salary Range: $110,000-$130,000 depending on experience
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Find Mid Level Data Manager JobsMid Level Data Manager Job Market
Who's Hiring
- Amazon186
- Apple89
- Speechify89
- Google77
- Booz Allen Hamilton57
Top Industries Hiring
- Technology & Software984
- Consulting & Professional Services445
- Retail300
- Banking & Financial Services251
- E-Commerce & Online Marketplaces219
Mid Level Data Manager Jobs: Frequently Asked Questions
How do I get a mid level data manager job?
Position yourself around ownership and impact, not just task completion. Highlight projects where you managed data quality, led a pipeline build, or delivered insights that shaped a business decision. Tailor your resume to show scope, not just tools. Mid level hiring managers want to see that you can work with minimal supervision and hold accountability for outcomes across a data workflow.
Which companies hire mid level data managers?
Companies hiring mid level data managers right now include Amazon, Apple, and Speechify, based on current listings on Migrate Mate as of July 2026. Hiring at this level comes from a wide range of employers, from large enterprises with dedicated data teams to mid-size organizations building out their data infrastructure for the first time.
Are there remote mid level data manager jobs?
Yes, and the share is meaningful. About 42% of mid level data manager openings are remote or hybrid as of July 2026, reflecting how broadly the role has shifted to distributed work. Fully remote roles tend to concentrate at organizations with established remote cultures, while hybrid arrangements are common at companies with on-site data infrastructure or stakeholder-facing responsibilities.
How do I move up to a mid level data manager role?
Growth from entry level to mid level comes from progressively owning more of the data lifecycle. That means moving from executing assigned tasks to designing pipelines, catching quality issues before they escalate, and communicating findings directly to stakeholders. Building depth in a core tool set, taking on small mentorship responsibilities, and demonstrating consistent delivery on projects with real business consequences are what distinguish a mid level candidate from a junior one.
Which industries hire the most mid level data managers?
Mid Level data manager roles concentrate in Technology & Software, Consulting & Professional Services, and Retail, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they operate at data volumes that require dedicated ownership rather than ad hoc management, and their compliance, reporting, or customer analytics demands call for professionals who can run data workflows with confidence.