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Data Science Assistant Jobs in Pennsylvania (NOW HIRING)

PassFort

Asst Dir - Data Scientist

King Of Prussia, PA · On-site

$100 - $130/hr

D. in Computer Science, Statistics, Applied Mathematics, Economics, Finance, Operations Research, or a related quantitative field; or a master's degree in any of these fields, with 2‑3 years of ...

慨正橡扯

Asst Dir - Data Scientist

King Of Prussia, PA · On-site

$116.50 - $169/hr

Ph.D. in Computer Science, Machine Learning, Natural Language Processing, Statistics, or a related quantitative field; or Master's degree with 2-3 years of experience in machine learning evaluation ...

The Pennsylvania State University

... Assistants. Responsibilities: Provide on-demand scientific expertise and support to NCEMS ... Proficiency in computational and data science methods relevant to advancing NCEMS Working Group ...

The Pennsylvania State University

This effort aims to strengthen the University's leadership in computational and data-driven ... Assistant professors should show early promise in teaching or research through emerging scholarly ...

The Pennsylvania State University

$115K - $173K/yr

As part of our Geospatial Image and Data Science Division, this highly collaborative team is ... * Assist our research efforts to develop novel sensing and estimation strategies that facilitate ...

Aegon

Lead Data Engineer

Philadelphia, PA · On-site

$115K - $138K/yr

Work collaboratively with other engineers, data scientists, analytics teams, and business product ... applications. * Assist the selection and integration of data related tools, frameworks and ...

Reply

Manager, Data Engineering

Philadelphia, PA · On-site

As a technical leader, the person will assist with setting the technical direction of the practice ... Bachelor's degree in computer science or related field * 12 years of industry experience, with 4 ...

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Data Science Assistant information

What is a data science assistant?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a data science assistant?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

How does a data science assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Data Science jobs in Pennsylvania? The most popular types of Data Science jobs in Pennsylvania are:
What are popular job titles related to Data Science Assistant jobs in Pennsylvania? For Data Science Assistant jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in Pennsylvania look for? The top searched job categories for Data Science Assistant jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Data Science Assistant jobs? Cities in Pennsylvania with the most Data Science Assistant job openings:
Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in Pennsylvania as of August 2026, with employment types broken down into 6% Internship, 79% Full Time, 9% Part Time, 3% Temporary, and 3% Contract. Highlights an 94% In-person, and 6% Remote job distribution.

Asst Dir - Data Scientist

PassFort

King Of Prussia, PA • On-site

$100 - $130/hr

Other

Posted 4 days ago

Job description

Moody’s is advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

Skills and Competencies
  • Hands‑on experience building, training, and evaluating deep‑learning models, with familiarity of modern architectures such as transformers, sequence and representation‑learning models.
  • Ability to explain complex modeling work clearly to senior leaders, cross‑functional partners, and non‑technical stakeholders, in both writing and speech.
  • Strong programming skills in Python or R.
  • Depth in one or more deep‑learning domains relevant to our work: representation learning for structured financial data, NLP for filings/news/unstructured text, or forecasting for macro and financial time series (Preferred).
  • Exposure to cloud platforms such as AWS, GCP, or Azure (Preferred).
  • Experience developing and deploying models on large, complex real‑world datasets: financial statements, macro time series, text, and other unstructured sources (Preferred).
  • Ability to own the full model‑development lifecycle: conceptualization, data exploration, design, estimation, validation, deployment, user training, and monitoring (Preferred).
  • Research output: publications, conference work, or open‑source contributions (Preferred).
Education
  • Ph.D. in Computer Science, Statistics, Applied Mathematics, Economics, Finance, Operations Research, or a related quantitative field; or a master’s degree in any of these fields, with 2‑3 years of experience in the financial industry.
Responsibilities
  • Partner across Moody’s business lines to enhance modeling and analytical frameworks, incorporating state‑of‑the‑art ML and deep‑learning techniques.
  • Design and deliver innovative analytical solutions, leveraging deep learning and quantitative methods to address complex financial, economic, and operational problems.
  • Identify opportunities for automation and model‑based decision enhancement, applying neural networks, representation learning, and statistical methods to improve accuracy, efficiency, and performance.
  • Collaborate with cross‑disciplinary teams to build scalable, cloud‑based analytical platforms grounded in clean, well‑engineered data.
  • Apply deep expertise in statistical, machine learning, and deep‑learning methods to develop insights and decision frameworks for internal stakeholders and clients.
  • Provide technical leadership, advising business partners on modeling strategy, trade‑offs, and the appropriate role of deep learning in analytical solutions.
  • Communicate technical subject matter clearly and concisely, ensuring that insights, limitations, and implications are well understood by diverse audiences.
About the Team

The Credit Center of Excellence (COE) at Moody’s is dedicated to developing, enhancing and maintaining our industry‑leading credit analytics and predictive modelling capabilities. Our analytics and models are used by institutions worldwide to make credit, risk management, pricing, and investment decisions. We are a global team that works closely with product management, commercial strategy, and go‑to‑market leaders to ensure high‑quality credit risk assessments and solutions.

Moody’s is an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody’s Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

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