1

Data Science Machine Learning Jobs in Pennsylvania

The Data Science Consultant role involves solving data problems end to end, utilizing machine learning and data analysis to enhance customer value and drive business growth. Responsibilities : • ...

The Data Science Consultant role involves solving data problems end to end, utilizing machine learning and data analysis to enhance customer value and drive business growth. Responsibilities : • ...

Senior Machine Learning Engineer

Pittsburgh, PA

$118.90K - $156.80K/yr

Collaborate closely with fellow taxonomists, software engineers, data scientists, data engineers ... Machine Learning or a related field Required Skills: * Minimum 3 years experience with hands-on ...

Senior Machine Learning Engineer

Pittsburgh, PA

$118.90K - $156.80K/yr

Collaborate closely with fellow taxonomists, software engineers, data scientists, data engineers ... Machine Learning or a related field Required Skills: * Minimum 3 years experience with hands-on ...

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118.90K - $156.80K/yr

Collaborate closely with fellow taxonomists, software engineers, data scientists, data engineers ... Machine Learning or a related field Required Skills: * Minimum 3 years experience with hands-on ...

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

next page

Showing results 1-20

Data Science Machine Learning information

See Pennsylvania salary details

$37.6K

$123K

$197K

How much do data science machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for data science machine learning in Pennsylvania is $123,033.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $136,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a Data Science Machine Learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

What are popular job titles related to Data Science Machine Learning jobs in Pennsylvania? For Data Science Machine Learning jobs in Pennsylvania, the most frequently searched job titles are:
Infographic showing various Data Science Machine Learning job openings in Pennsylvania as of May 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 53% Physical, 4% Hybrid, and 43% Remote job distribution, with an average salary of $123,033 per year, or $59.2 per hour.
Machine Learning Engineer, Specialist

Machine Learning Engineer, Specialist

Vangard, Inc.

Malvern, PA

$112.40K - $134.90K/yr

Full-time

Posted 3 days ago


Job description


Responsibilities:

  • Develops complex data pipelines and implements data engineering design principles for iterative data pipeline development to drive scale and efficiency. Proficient in model development environments and coding best practices to enable model deployment.

  • Integrates and optimizes existing data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Proficient in SDLC processes and related tools and technologies.

  • Partners with data science teams to review model ready dataset document/feature documentation. Develops data model design and document and reviews for completeness with data science teams.

  • Partners with data science teams to understand data requirements, performs data discovery for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs. Drives efficiency through the use of data discovery tools.

  • Engages with internal stakeholders to understand and probe business processes and develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.

  • Writes model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and triages issues. Coordinates and plans response to model monitoring alerts and resolves issues.

  • Serves as a machine learning engineering subject matter expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.

  • Participates in special projects and performs other duties as assigned.

  • Designs and implements statistical analysis frameworks and protocols to uncover business trends across functions like marketing, supply chain, and economics.

  • Applies advanced data mining techniques to build scalable models for deriving actionable insights from large-scale data sets.

  • Explores and integrates evolving methodologies in machine learning and big data science to enhance decision-making strategies.


Qualifications:

  • Minimum 8 years of experience in machine learning engineering or data science roles

  • Bachelor's degree (B.E./B.Tech) in Computer Science, Data Engineering, AI/ML, or related fields, or a Master's degree/Diploma in Computer Science or Data Science

  • Strong expertise in data pipeline development, statistical modeling, SDLC, AI/ML concepts, model monitoring, and stakeholder engagement across domains

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.