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Data Scientist Project Manager Jobs in Rhode Island

Sr Manager, Data Science

Woonsocket, RI · On-site +1

$140K - $260K/yr

Directs activities of data science projects, including resource allocation, budget management, and timeline adherence, ensuring successful project execution. Analyzes organization to strategize and ...

Project Manager

Providence, RI · On-site

$100K - $155K/yr

Thorough completion of all financial data with an eye to quickly identify potential/existing issues ... Experience building projects specifically in Life Science, Advanced Tech / Manufacturing Commercial ...

Collaborate with engineering, product, and data science teams to understand requirements ... Take ownership of assigned projects and deliver high-quality results with urgency, while ...

Project Manager

Providence, RI · On-site

$100K - $155K/yr

Thorough completion of all financial data with an eye to quickly identify potential/existing issues ... Experience building projects specifically in Life Science, Advanced Tech / Manufacturing Commercial ...

Project Manager

Providence, RI · On-site

$100K - $155K/yr

Thorough completion of all financial data with an eye to quickly identify potential/existing issues ... Experience building projects specifically in Life Science, Advanced Tech / Manufacturing Commercial ...

CFG is a leading financial institution dedicated to providing innovative solutions to manage ... Partner with data science teams under leadership guidance to deliver model solutions * Create and ...

Prepare and manage project plans that encompass data conversion, product customization/software releases, environment preparation, and production deployment including training, configuration, testing ...

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Data Scientist Project Manager information

What is a data scientist project manager?

A Data Scientist Project Manager is a professional who oversees data science projects from conception through completion, ensuring that project goals align with business objectives. They bridge the gap between data science teams and stakeholders, managing timelines, resources, and communication. In addition to technical knowledge in data science and analytics, they possess strong project management skills to coordinate tasks, mitigate risks, and deliver results. Their role is essential for translating complex data-driven insights into actionable business strategies. They often use methodologies like Agile or Scrum to guide project workflows and adapt to changing requirements.

What are the key skills and qualifications needed to thrive as a data scientist project manager?

To thrive as a Data Scientist Project Manager, you need a solid background in data science, analytics, and project management, often supported by degrees in computer science, statistics, or business and certifications like PMP or Agile. Familiarity with tools such as Python, R, SQL, project management software (e.g., Jira, Trello), and cloud platforms is crucial. Excellent communication, leadership, and problem-solving abilities help bridge gaps between technical teams and stakeholders. These skills ensure successful project delivery by aligning data-driven insights with business objectives and effective team coordination.

How do data scientist project managers typically balance technical data work with project management responsibilities?

Data Scientist Project Managers often split their time between hands-on data analysis and overseeing project progress. They commonly coordinate with cross-functional teams, set project timelines, and ensure that data solutions align with business objectives while occasionally contributing code or analytical insights. Effective communication and time management are essential, as they must bridge the gap between technical teams and stakeholders. This dual responsibility offers exposure to both technical growth and leadership development, making it ideal for professionals seeking advancement into higher management roles.

What is the difference between Data Scientist Project Manager vs Data Analyst Project Manager?

AspectData Scientist Project ManagerData Analyst Project Manager
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related fields; certifications like PMP or AgileBachelor's in Data Analysis, Business, or related fields; certifications like PMP or Agile
Work EnvironmentLeads data science projects, collaborates with data scientists and engineersManages data analysis projects, works with analysts and business teams
Employer & Industry UsageTech companies, finance, healthcare, industries with advanced analyticsRetail, marketing, finance, industries relying on data reporting

The main difference is that Data Scientist Project Managers oversee data science initiatives involving complex modeling and algorithms, while Data Analyst Project Managers focus on managing data reporting and analysis projects. Both roles require project management skills and relevant certifications, but their technical focus and team collaboration differ.

Can a data scientist become a project manager?

A data scientist can transition to a project manager role by developing skills in leadership, communication, and project planning, often supported by certifications like PMP or Agile. Their technical expertise can be valuable in managing data-driven projects, but they typically need to gain experience in managing teams and project workflows.

What are popular job titles related to Data Scientist Project Manager jobs in Rhode Island?

For Data Scientist Project Manager jobs in Rhode Island, the most frequently searched job titles are:

What job categories do people searching Data Scientist Project Manager jobs in Rhode Island look for?

The top searched job categories for Data Scientist Project Manager jobs in Rhode Island are:

What cities in Rhode Island are hiring for Data Scientist Project Manager jobs?

Cities in Rhode Island with the most Data Scientist Project Manager job openings:

Data Scientist (Statistician)

Providence, RI


Criminal Investigation & Law Enforcement | IRS Careers
Public Administration • 10K+ employees

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$125K/yr

Full-time

Posted 3 days ago

New


Job description

WHAT IS LARGE BUSINESS AND INTERNATIONAL?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s):
    • LBI - ADCCI - Compliance Planning & Analytics (CP&A), Workload Development & Delivery (WDD). Team will be determined at time of selection.

REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:

  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.


AND
You must also meet the following requirement(s):

  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03 or 04 positions.


For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER


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