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Data Science Machine Learning Jobs in Pennsylvania

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent combination of training ...

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with ten (10) years of experience or equivalent combination of training ...

Associate Data Scientist

Pittsburgh, PA · On-site

$57K - $57K/yr

Requirements: * BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training ...

Responsibilities : • Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors. • Define and execute data science strategies ...

Lead and develop high-performing teams of data scientists, machine learning engineers, researchers, and technical contributors. * Define and execute data science strategies that advance scientific ...

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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 Jul 23, 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 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 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.
Infographic showing various Data Science Machine Learning job openings in Pennsylvania as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $123,033 per year, or $59.2 per hour.
Senior Data Scientist (Machine Learning & Generative AI)

Senior Data Scientist (Machine Learning & Generative AI)

MSD

West Point, PA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Job description

Job Description

Job Summary:

As a Senior Data Scientist, you will leverage your expertise in machine learning model development, generative AI, and software engineering to rapidly prototype and deploy advanced analytics products for our manufacturing division. You will collaborate with cross-functional teams, including IT, engineering, and operations, to design and implement robust advanced analytics solutions at scale within production systems. You will also engage in ad-hoc consulting roles to support various projects across the organization. Our data science team contributes to different project phases, from ideation and business case development, through data discovery and preparation, to model development, prototyping, and facilitating adoption.

Primary Job Responsibilities:

  • Independently design and develop innovative quantitative methodologies, leveraging different methods and approaches in machine learning, deep learning, and generative AI, to drive data-driven decision-making and influence key initiatives within the company.

  • Apply data science, machine learning, and deep learning techniques to create tools for process monitoring, process optimization, and predictive analytics.

  • Develop end-to-end digital solutions, including automation of data workflows and integration into existing systems.

  • Engage with customers and stakeholders to understand their needs, requirements, expectations, and potential opportunities, ensuring alignment with business objectives.

  • Build and disseminate in-depth domain knowledge of emerging trends in one or more sub-specialty areas of data analytics, fostering collaboration with cross-functional stakeholders.

  • Design, lead, and document the development of analytics applications, platforms, and processes to unlock value through scientific insights.

  • Stay updated on current best practices, methodologies, and technologies in AI, machine learning, and data science landscape, including compliance and ethical considerations.

Required Skills:

  • Extensive knowledge of both traditional supervised and unsupervised machine learning algorithms, as well as familiarity with advanced deep learning architectures.

  • Proven hands-on experience with Python, including practical skills with libraries such as scikit-learn, Keras, TensorFlow, or PyTorch.

  • Familiarity with feature engineering and exploratory data analysis for both structured and unstructured data sets.

  • Knowledge of experiment tracking methodologies and tools to monitor model performance and maintain reproducibility.

  • Exceptional communication skills to effectively convey complex information to both technical and non-technical stakeholders.

  • A strong software engineering mindset, emphasizing the importance of producing high-quality code, documentation, and pipelines.

  • A data-centric mindset, focusing on how data can be leveraged to create actionable insights and drive business value.

  • Experience working within Agile frameworks and methodologies.

Preferred Qualifications:

  • Understanding of generative AI including large language models and vision language models, RAG, pre-training, and/or fine-tuning for specific applications.

  • Experience with agents, agentic AI platforms (CrewAI, LangGraph, LangChain, AutoGen, Semantic Kernel, Bedrock, Strands, etc), agent tooling and protocols (MCP, A2A), and/or AI coding tools (Claude Code, Cursor, Codex, Open Claw)

  • Familiarity with graph networks, semantic layers, and causal inference.

  • Familiarity with deep learning applications or inference, computer vision, autoencoders, etc.

  • Familiarity with modern MLOps tools and best practices for lifecycle management including CI/CD pipelines, containerization technologies such as Docker, and deploying machine learning models in cloud environments such as AWS, Databricks, or similar platforms.

Education:

  • Bachelor's degree required

  • Preferred Ph.D. in chemical engineering, applied mathematics, or other technical fields with expertise in data science and machine learning projects or master's degree in data science, computer science, applied statistics/mathematics, chemical engineering, or a related field with 2+ years of relevant experience in data science and machine learning projects.

Required Skills:

Agile Methodology, Agile Methodology, Applied Mathematics, Business Analytics, Business Case Development, Change Catalyst, Chemical Engineering, Cheminformatics, Compliance Analytics, Containerization, Cross-Functional Collaboration, Data Mining, Data Science, Detail-Oriented, Emerging Trends, Generative AI, Information Architecture Design, Information Systems Engineering, Machine Learning (ML), Modeling Simulations, Pharmacogenetics, Predictive Modeling, Prototyping, Software Tool Development, Stakeholder Engagement {+ 2 more}

Preferred Skills:

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

EEOC Know Your Rights

EEOC GINA Supplement

We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively.

Learn more about your rights, including under California, Colorado and other US State Acts

The salary range for this role is

$129,000.00 - $203,100.00

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.

You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.

San Francisco Residents Only:We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only:We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance

Search Firm Representatives Please Read Carefully
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status:

Regular

Relocation:

Domestic

VISA Sponsorship:

No

Travel Requirements:

No Travel Required

Flexible Work Arrangements:

Hybrid

Shift:

Not Indicated

Valid Driving License:

No

Hazardous Material(s):

N/A

Job Posting End Date:

07/21/2026

*A job posting is effective until 11:59:59PM on the day BEFOREthe listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.