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R Data Scientist Assistant Jobs in Wisconsin (NOW HIRING)

WI ยท On-site

$150 - $200/hr

Senior Data Scientist - Applied AI, NLP, and LLM Solutions Note: Fidelity will not provide ... assistants, recommender systems, and anomaly detection. The successful candidate must be ...

WI ยท On-site

$150 - $200/hr

Delivers expert work in General R, D & I with high quality and timeliness, applying best practices ... Master's degree in Computer Science, Artificial Intelligence, Software Engineering, DataScienceor a ...

WI ยท On-site

$125 - $150/hr

Delivers expert work in General R, D & I with high quality and timeliness, applying best practices ... Master's degree in Computer Science, Artificial Intelligence, Software Engineering, DataScienceor a ...

WI ยท On-site

$125 - $150/hr

... assist in the resolution of technical issues * Developing and delivering complex technical ... EEO Scientific Research Corporation is an equal opportunity employer that does not discriminate in ...

New

Senior Data Scientist

Brookfield, WI ยท On-site

$132K - $155K/yr

... science, engineering or applied mathematics, or equivalent work experience - Six to eight years of ... R/SAS/SQL for data extraction, data mining, and predictive analytics - Demonstrated project ...

Showing results 21-40

R Data Scientist Assistant information

What is an R Data Scientist Assistant?

R Data Scientist Assistants are professionals who support data scientists by performing data cleaning, analysis, and visualization tasks using the R programming language. They help prepare datasets, create scripts, generate reports, and may assist in implementing machine learning models. Their role is crucial in ensuring data quality and streamlining the workflow, allowing data scientists to focus on more complex analyses. This position typically requires a strong foundation in statistics, programming in R, and good communication skills.

What are the typical collaboration dynamics between an R Data Scientist Assistant and senior data scientists or analysts?

As an R Data Scientist Assistant, you will often work closely with senior data scientists and analysts, supporting them by preparing datasets, performing initial data cleaning, and conducting exploratory analyses using R. You may be responsible for creating reproducible scripts, visualizing results, and documenting your workflow. Regular meetings and code reviews are common, providing opportunities to learn best practices and receive feedback. This collaborative environment helps you build technical skills and understand how your contributions fit into larger data-driven projects.

What are the key skills and qualifications needed to thrive as an R Data Scientist Assistant, and why are they important?

To thrive as an R Data Scientist Assistant, you need a solid understanding of statistics, data analysis, and proficiency in the R programming language, often supported by coursework in data science or a related field. Familiarity with tools such as RStudio, data visualization packages like ggplot2, and version control systems like Git is typically expected. Strong attention to detail, critical thinking, and effective communication skills help you interpret data and work collaboratively with teams. These skills are crucial for ensuring accurate data analysis, efficient workflow, and actionable insights for business or research objectives.

What is the difference between R Data Scientist Assistant vs Data Analyst?

AspectR Data Scientist AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related field; familiarity with RBachelor's in Data, Statistics, Business, or related field; proficiency in data tools
Work EnvironmentResearch labs, tech companies, analytics teamsBusiness settings, marketing, finance, healthcare
Employer & Industry UsageTech firms, research institutions, analytics departmentsCorporations, consulting firms, government agencies
Common Search & ComparisonOften compared for entry-level data roles involving RCompared for data interpretation and reporting tasks

The R Data Scientist Assistant typically focuses on supporting data science projects using R, requiring programming skills and statistical knowledge. Data Analysts often handle data interpretation, reporting, and visualization across various industries. While both roles require analytical skills, the assistant role emphasizes programming and statistical modeling, whereas the analyst role centers on data reporting and business insights.

What are the most commonly searched types of R Data Scientist jobs in Wisconsin?

The most popular types of R Data Scientist jobs in Wisconsin are:

What cities in Wisconsin are hiring for R Data Scientist Assistant jobs?

Cities in Wisconsin with the most R Data Scientist Assistant job openings:

$150 - $200/hr

Other

Posted 17 days ago


Job description

Job Description: Senior Data Scientist โ€“ Applied AI, NLP, and LLM Solutions

Note: Fidelity will not provide immigration sponsorship for this position Fidelity Workplace Investing is seeking handsโ€‘on, builderโ€‘oriented Senior Data Scientists with experience in applied AI, natural language processing, large language models, machine learning, and knowledge graph technologies. This position will be based full time in either Westlake, TX or Merrimack, NH.

The Purpose of Your Role

This individual will lead highโ€‘profile applied data science and artificial intelligence initiatives across Workplace Investing, working closely with Technology, Product Management, AI/ML Engineering, and others. The role will focus on developing and evaluating AIโ€‘based solutions using natural language processing (NLP), large language models (LLM), machine learning (ML), knowledge graphs, agentic AI patterns, and other advanced or emerging techniques. Key assignments may include document processing and information extraction, schema mapping, enterprise assistants, recommender systems, and anomaly detection. The successful candidate must be comfortable operating in a fastโ€‘paced and sometimes ambiguous environment working with current and emerging AI technologies. They will be expected to gather and analyze data from multiple structured and unstructured data sources, develop reliable models and evaluation frameworks, interpret and clearly communicate findings to technical and business audiences. They will support a broad range of applied AI initiatives with the highest degree of quality, partner effectively with engineering teams to move solutions into production, and thrive in a highโ€‘performing, collaborative work environment. The ideal candidate combines strong data science fundamentals with product instincts, technical curiosity, and a track record of delivering measurable business impact.

The Skills You Bring
  • PhD in Computer Science, Information Science, Statistics, or a related STEM discipline with focus on AI, machine learning, natural language processing, deep learning, knowledge graphs, or related methods
  • OR a Masterโ€™s Degree in a related field with 3 or more years relevant professional experience
  • Strong technical foundation in machine learning and statistical modeling, with deeper experience in one or more applied AI areas such as natural language processing, large language models, deep learning, knowledge graphs, or related methods.
  • Strong Python and SQL programming skills with demonstrated proficiency in data extraction, data engineering, exploratory analysis, feature engineering, data modeling, pipeline automation, and model evaluation.
  • Solid verbal communication, presentation, and technical writing skills with an ability to explain complex data science, statistics, and computer science concepts clearly to nontechnical audiences.
  • Experience or working knowledge in one or more applied AI areas such as information retrieval, question answering, chatbot evaluation, retrieval-augmented generation, or agentic AI frameworks.
  • Exposure to intelligent document processing use cases, which may include document classification, OCR, key-value extraction, signature or seal detection, annotation strategy and dataset creation, and evaluation of extraction quality.
  • Working knowledge of embedding models, vector representations, semantic similarity clustering, or dimensionality reduction techniques such as t-SNE or UMAP.
  • Experience in one or more predictive modeling areas such as recommendation systems, ranking models, ensemble methods, anomaly detection, statistical process control, time-series monitoring, threshold strategies, or alert-quality evaluation.
  • Experience designing or contributing to AI/ML evaluation and monitoring frameworks, including benchmark datasets, labeled and synthetic test data, model and prompt comparison, precision/recall analysis, error analysis, latency assessment, cost-quality tradeoff analysis, and production monitoring with tools such as Fiddler.
The Value You Deliver
  • Lead the data science and model development components of projects involving large language models, natural language processing, knowledge graphs, and related applied techniques.
  • Design, build, and deploy applied AI solutions across NLP, LLMs, document processing, schema mapping, recommendation, and anomaly detection use cases.
  • Lead data analysis with diverse scope and complex business and technical challenges.
  • Develop best practices for data science, considering the full analytical lifecycle.
  • Ensure the delivery of high-quality, trustworthy data science by developing guidelines and rigorous evaluation frameworks for AI/ML solutions.
  • Implement new technologies in a production environment with product, IT, and data engineering teams.
  • Present reports and findings to senior-level technical and nontechnical audiences.
How Your Work Impacts the Organization

As a data scientist in Fidelity Workplace Investing, you will contribute to advancing the analytics and data science capability for a variety of employee benefit products and will take the organization to the next level. Fidelityโ€™s Onsite Working Model Fidelity is transitioning to a fullโ€‘time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications

Category: Data Analytics and Insights

Please be advised that Fidelityโ€™s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirementโ€‘related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

At Fidelity, we are passionate about making our financial expertise broadly accessible and effective in helping people live the lives they want! We are a privately held company that places a high degree of value in creating and nurturing a work environment that attracts the best talent and reflects our commitment to our associates. We are proud of our diverse and inclusive workplace where we respect and value our associates for their unique perspectives and experiences.

Fidelity Investments is an equal opportunity employer. Fidelity will reasonably accommodate applicants with disabilities who need adjustments to participate in the application or interview process. To initiate a request for an accommodation please contact the following: For roles based in the US: Contact the HR Leave of Absence/Accommodation Team by sending an email to accommodations@fmr.com, or by calling 800-835-5099, prompt 2, option 2 For roles based in Ireland: Contact AccommodationsIreland@fmr.com For roles based in Germany: Contact Accommodationsgermany@fmr.com Fidelity Privacy Policy

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