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Remote Director Machine Learning Jobs in Radnor, PA

Dlapiper

Data Scientist

Philadelphia, PA · On-site +1

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Posted today

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$144K - $250K/yr

Advanced machine learning modeling and/or technical expertise in developing market differentiation ... Senior Manager and above Direct Reports : 0 Work Environment * Normal office environment. (Remote ...

Ivy Rehab Network

Associate Data Scientist

Philadelphia, PA · On-site +1

$59K - $60K/yr

Strong Machine Learning Fundamentals: * Supervised Learning: Algorithms where the data is labeled ... Hybrid and remote work flexibility. * Empowering Values: Live by values that prioritize teamwork ...

New

GATE 1 LTD

A.I. Manager

Fort Washington, PA · On-site +1

Build and lead a remote AI team, including recruiting, mentoring, and performance management ... Guide model development, including machine learning, deep learning, NLP, and generative AI ...

GATE 1 LTD

A.I. Manager

PA · On-site +1

Build and lead a remote AI team, including recruiting, mentoring, and performance management ... Guide model development, including machine learning, deep learning, NLP, and generative AI ...

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Showing results 21-40

All JobsMachine Learning JobsRemote Director Machine Learning JobsRemote Director Machine Learning Jobs in Radnor, PA

Remote Director Machine Learning information

See Radnor, PA salary details

$32.5K

$83K

$127.2K

How much do remote director machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote director machine learning in Radnor, PA is $82,956.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,500.00 and $95,600.00 per year, depending on experience, location, and employer.

What does a remote director of machine learning do?

A Remote Director of Machine Learning leads teams of data scientists and engineers to develop, implement, and oversee machine learning solutions for an organization, all while working remotely. They are responsible for setting the strategic direction for ML projects, collaborating with stakeholders, and ensuring that models align with business objectives. This role typically involves both technical leadership—such as reviewing algorithms and architectures—and managerial duties, such as mentoring staff and managing budgets. Working remotely, they use digital collaboration tools to communicate, monitor progress, and deliver results effectively.

How does a remote director of machine learning typically coordinate and lead distributed teams across different time zones?

As a Remote Director of Machine Learning, effective coordination of distributed teams requires strong communication strategies, including regular video meetings, clear documentation, and use of collaborative project management tools. Leaders in this role often establish overlapping core hours and leverage asynchronous communication to accommodate various time zones. They focus on aligning goals, fostering a culture of transparency, and ensuring continuous progress through well-defined milestones. Building trust and maintaining team engagement remotely are common challenges, but successful directors prioritize mentorship, feedback, and virtual team-building activities to create a cohesive work environment.

What are the key skills and qualifications needed to thrive as a remote director of machine learning, and why are they important?

To thrive as a Remote Director of Machine Learning, you need advanced expertise in machine learning algorithms, data science, and leadership, typically supported by a graduate degree in a related field and extensive experience in deploying ML solutions. Familiarity with tools like Python, TensorFlow, PyTorch, cloud platforms, and experience with project management systems is essential, and certifications such as AWS Certified Machine Learning can be advantageous. Outstanding communication, strategic thinking, and the ability to mentor and manage distributed teams are crucial soft skills in this role. These skills and qualities are vital to successfully lead innovative ML projects, align technical teams with business goals, and drive impactful outcomes in a remote environment.

What is the difference between Remote Director Machine Learning vs Remote Data Science Manager?

AspectRemote Director Machine LearningRemote Data Science Manager
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related field; experience in ML algorithmsMaster's in Data Science, Statistics, or related; strong analytical background
Work EnvironmentLeads ML teams, develops models, and oversees deployment in tech-focused companiesManages data science teams, focuses on insights and analytics for business decisions
Employer & Industry UsageTech firms, AI startups, large enterprises with AI initiativesFinancial, healthcare, retail, and other industries leveraging data insights

While both roles require advanced education and involve data-driven work, the Remote Director Machine Learning primarily focuses on leading ML model development and deployment, whereas the Remote Data Science Manager emphasizes managing data analysis teams and deriving business insights.

What cities near Radnor, PA are hiring for Remote Director Machine Learning jobs?

Cities near Radnor, PA with the most Remote Director Machine Learning job openings:

Remote Director Machine Learning jobs near you
Infographic showing various Remote Director Machine Learning job openings in Radnor, PA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 27% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $82,956 per year, or $39.9 per hour.

Data Scientist

Dlapiper

Philadelphia, PA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 14 hours ago

Posted today

Job description

DLA Piper is, at its core, bold, exceptional, collaborative and supportive. Our people are the backbone, heart and soul of our firm. Wherever you are in your professional journey, DLA Piper is a place you can engage in meaningful work and grow your career. Let's see what we can achieve. Together.

Summary
Position is responsible for data collection, data exploration and using large data sets to find opportunities for improving business outcomes. Designs data modeling processes to create algorithms and predictive models. Performs custom analysis. Uses modelling to drive business results with data-based insights and tests the effectiveness of different courses of action.

Location

This position can sit in any of our US offices.


Responsibilities

  • Works with internal stakeholders and clients to identify opportunities for leveraging organizational data to drive business solutions.
  • Prioritizes, scopes and manages data science projects for internal stakeholders and clients.
  • Mines and analyzes data to drive optimization and improvement of product development, marketing techniques and business strategies.
  • Assesses the effectiveness and accuracy of new data sources and data gathering techniques.
  • Applies the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering. Identifies patterns and looks for opportunities for optimization.
  • Develops custom data models and algorithms to apply to data sets.
  • Uses predictive modeling to increase and optimize client opportunities and business outcomes.
  • Writes computer programs and analyzes large datasets to uncover answers to complex problems.
  • Develops testing frameworks and tests model quality.
  • Coordinates with different functional teams to identify and implement models and monitor outcomes.
  • Develops processes and tools to monitor and analyze modeling performance and data accuracy.
  • Establishes best practices for data analysis and reporting.
  • Other duties as assigned.


Skills and Competencies

  • A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred. Must be self-driven, curious and creative.
  • Experience must include creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, data mining techniques, etc.
  • Experience with most or all of the following basic data science tools: Python, R, SQL, SAS, NLTK, Scikit-Learn, Excel, Tableau, Power BI, and Jupyter; Basic data science concepts: probability, statistics, hypothesis testing, machine learning, natural language processing, predictive modeling, data visualization; and Big data tools: Hadoop, Azure, etc.
  • Experience in a professional services or law firm is preferred. Must be adept in agile methodologies and well-versed in machine learning, artificial intelligence and constructing data science pipelines.
  • Demonstrated presentation skills along with strong business acumen. Ability to communicate actionable insights using data, often for a non-technical audience.


Education

  • Bachelor's degree in computer science, data science, statistics, applied mathematics or related field


Years of Experience

  • 5 years of relevant experience in applying data science techniques to business functions.


Essential Job Expectations

All DLA Piper employees are expected to demonstrate excellence in how we serve our clients and develop our people, upholding our firm values as part of our culture. Specific expectations include:

  • Communicate effectively, both verbally and in writing, with clients, lawyers, business professionals, and external audiences.
  • Produce high-quality work and respond to correspondence in an efficient, timely, and professional manner.
  • Meet deadlines, manage competing priorities, and commit to meeting high standards.
  • Comply with firm policies and procedures.
  • Maintain confidences as required in a law firm environment.


Physical Demands
Sedentary work: This is primarily sedentary work, requiring occasional exertion of up to 10 pounds of force to lift, carry, push, pull, or move objects. The role involves sitting for extended periods, with occasional walking and standing, and occasional travel, both domestic and international.
Work Environment

The firm's work location requirements may be modified at the firm's discretion. Opportunity for a hybrid work arrangement combining remote and in-office work. The specific arrangement will be determined at the time of hiring and may be modified at the firm's discretion.

Compensation & Benefits

The firm's expected hiring range for this position is $112,879 - $179,481 depending on the candidate's geographic location, experience, skills, educational background, and overall qualifications.

DLA Piper offers a comprehensive benefits package, including medical, dental, and vision insurance, 401(k) retirement plan, and additional benefits.

Application Process

Interested candidates must apply directly online. Application materials sent via email will not be accepted. Reasonable accommodations may be made upon request to enable individuals with disabilities to perform the essential functions of this position or participate in the selection process. For accommodation requests, please contact careers@us.dlapiper.com.

Agency applications will not be considered.

No immigration sponsorship is available for this position.

Disclaimer

This job description provides a concise overview of the role and is not intended to describe all work elements that may be performed. It should not serve as the sole criteria for personnel decisions. Job duties, requirements, and expectations may be modified at the firm's discretion at any time. This job description does not alter the at-will nature of employment.

We are committed to excellence in how we serve our clients and develop our people.

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DLA Piper is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.Job applicant poster viewing center.

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