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Temporary Computer Data Scientist Jobs in Pennsylvania

D. in Data Science, Computer Science, Engineering, Chemistry, Physics, or related field. * 5+ years of experience delivering AI/ML solutions in production environments * Strong expertise in:

Senior Data Scientist

Dallas, PA · On-site

$60K - $135K/yr

Senior Data Scientist City: Dallas State/Province: Texas Posting Start Date: 8/10/26 Wipro Limited ... Computer Science, Applied Mathematics, Statistics, etc.) Experience in Operations research is ...

$97K - $128K/yr

Bachelor's degree in Business or Computer Science, Analytics, Information Technology, Engineering, Management, or related field. * 7+ years of experience in data analytics, operations, or business ...

Showing results 41-60

Temporary Computer Data Scientist information

What is the difference between Temporary Computer Data Scientist vs Temporary Data Analyst?

AspectTemporary Computer Data ScientistTemporary Data Analyst
Required CredentialsBachelor's or higher in CS, Data Science, or related; often some experience with machine learningBachelor's in Statistics, Math, or related; proficiency in data visualization and basic analysis
Work EnvironmentTech companies, research labs, or consulting firms; project-based rolesBusiness, finance, marketing sectors; supporting decision-making processes
Employer & Industry UsageUsed across tech, healthcare, finance; often in innovative or R&D projectsCommon in corporate settings, retail, and marketing departments

Temporary Computer Data Scientists focus on advanced analytics, machine learning, and predictive modeling, requiring more technical expertise. Temporary Data Analysts primarily handle data collection, cleaning, and basic analysis to support business decisions. While both roles involve working with data, Data Scientists typically require stronger programming and statistical skills, whereas Data Analysts focus on reporting and visualization.

Can I get a temporary computer data scientist job with no experience?

Temporary computer data scientist roles typically require some experience in data analysis, programming, or related skills such as Python, R, or SQL. Entry-level positions may be available for those with relevant coursework, certifications, or strong analytical aptitude, but most employers prefer candidates with prior experience or demonstrated skills.

What are the most commonly searched types of Computer Data Scientist jobs in Pennsylvania?

The most popular types of Computer Data Scientist jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Temporary Computer Data Scientist jobs?

Cities in Pennsylvania with the most Temporary Computer Data Scientist job openings:

Full-time

Posted 16 days ago


United States Steel rating

7.6

Company rating: 7.6 out of 10

Based on 84 frontline employees who took The Breakroom Quiz

228th of 545 rated manufacturers


Job description

We are seeking a Senior Data Scientist, Finance Analytics to join the Finance Transformation team within Corporate FP&A. It is a hybrid position in Pittsburgh, PA. This role will design, build, and scale AI-enabled analytics solutions that modernize financial planning, forecasting, reporting, and decision support across USS. The ideal candidate brings a strong combination of finance acumen, advanced analytics, machine learning, automation, and applied generative AI experience. This is a high-impact opportunity to work at the intersection of Finance, data engineering, and AI to improve forecast accuracy, reduce manual effort, strengthen financial insights, and enable faster, more confident decision-making for senior leadership.
Responsibilities:

  • Design, develop, and maintain AI-enabled financial dashboards, analytics applications, and executive reporting tools using Databricks and related analytics platforms.
  • Build scalable ETL and ELT data pipelines that integrate financial, operational, and enterprise data into the Enterprise Data Platform.
  • Develop and validate machine learning models for financial forecasting, scenario analysis, variance analysis, anomaly detection, and business trend identification.
  • Apply generative AI and large language model capabilities to streamline financial reporting, management commentary, knowledge retrieval, and self-service financial analysis.
  • Automate recurring FP&A, monthly close, and management reporting processes to reduce manual effort and improve accuracy.
  • Partner with Corporate FP&A, segment finance teams, data engineering, and business stakeholders to translate financial questions into scalable analytics and AI solutions.
  • Prepare executive-ready analyses, insights, and narratives that support forecasting, financial steering, monthly close activities, and strategic decision-making.
  • Own end-to-end delivery of analytics initiatives, including requirements gathering, solution design, model development, testing, deployment, adoption, and ongoing performance monitoring.
  • Ensure AI and financial modeling outputs are explainable, auditable, traceable to source data, and aligned with finance governance standards.
  • Document model assumptions, data definitions, controls, business rules, and process requirements as analytics capabilities scale.
  • Mentor junior team members on data science, financial analytics, responsible AI, and engineering best practices.

Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Engineering, Finance, Economics, Statistics, Mathematics, or a related field; Master's degree preferred.
  • 3-5 years of experience in data science, financial analytics, FP&A analytics, or a related quantitative role.
  • Advanced proficiency in Python and SQL, including experience writing production-grade, testable code and building complex financial data pipelines.
  • Hands-on experience developing, validating, and monitoring machine learning models, with emphasis on forecasting, regression, classification, anomaly detection, or optimization use cases.
  • Experience building and validating time-series forecasting models, including back testing, feature selection, model interpretability, and overfit prevention.
  • Familiarity with AI and machine learning libraries and frameworks such as Scikit-learn, PyTorch, TensorFlow, MLflow, LangChain, or similar tools.
  • Experience applying generative AI or LLM-based solutions to business workflows, financial reporting, knowledge retrieval, commentary generation, or analytics automation preferred.
  • Hands-on experience with a modern cloud-based analytics platform such as Databricks or Snowflake and a major cloud provider such as Azure, AWS, or GCP.
  • Experience with Power BI, Tableau, or other BI tools, including financial dashboard development and KPI visualization, preferred.
  • Exposure to financial systems such as OneStream, Oracle GL/EPM, SAP, ERP, EPM, or similar platforms preferred.
  • Strong understanding of financial planning, forecasting, budgeting, variance analysis, cost drivers, profitability analysis, or management reporting preferred.
  • Familiarity with LLM-powered code assistants, such as Codex, GitHub Copilot, Claude Code, or similar tools.
  • Ability to explain complex models and analytical outputs to Finance leaders and non-technical stakeholders in a clear, practical, and business-relevant manner.
  • Manufacturing, industrial, or capital-intensive industry experience a plus.
     
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Since 1901, U. S. Steel has been a recognized leader in steel production. Today, as the first North American steel company to have declared a 2050 net-zero greenhouse gas emissions goal, we remain as innovative as ever, leading transformation across our industry while continuing to make products for everyday life - from industries as far ranging as automotive, construction, containers and packaging, appliances, and energy.
Underneath it all is our Culture of Caring, which shows up in our community partnerships, charitable contributions, company-sponsored employee volunteer initiatives, scholarship programs, leadership training, and much more. And of course, it takes shape in a steadfast commitment to safety first in our workplaces and respect for our employees, who are United by Steel.
We are honored to have earned accolades and awards from well-regarded organizations, including the following:

  • Ethisphere's World's Most Ethical Companies 2022, '23, '24
  • Disability: IN's Best Places to Work for Disability Inclusion 2021, '22, '23, '24
  • Human Rights Campaign Foundation's Equality 100 Award 2020, '21, '22, '23-24, '25
  • Military Times' Best for Vets: Employers 2023, '24


Conducting business with integrity and with the highest ethical values has underpinned U. S. Steel's success for over 100 years, and it remains critical to our company's success in the future. U. S. Steel is an Equal Opportunity Employer. It is our policy to provide equal employment opportunity (EEO) according to job qualifications without discrimination on the basis of race, color, religion, ancestry, national origin, age, genetics, sexual orientation, sex, gender identity, disability status or status as a protected Veteran or any other legally protected group status. (California residents may visit www.ussteel.com/CANotice regarding collection of personal information and U. S. Steel's privacy practices.)


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