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Data Science Jobs in Westerly, RI (NOW HIRING)

ResultStack

Sr. Data Scientist

Carolina, RI · On-site

This is a high-impact role at the intersection of data science, operational expertise, and emerging AI. CORE REQUIREMENTS This candidate will have Dashboard & BI Tooling. Being Fluent in Tableau ...

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Data Science information

See Westerly, RI salary details

$37.8K

$123.6K

$197.9K

How much do data science jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data science in Westerly, RI is $123,638.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,200.00 and $137,000.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Westerly, RI? The most popular types of Data Science jobs in Westerly, RI are:
What cities near Westerly, RI are hiring for Data Science jobs? Cities near Westerly, RI with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Westerly, RI as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $123,638 per year, or $59.4 per hour.
Sr. Data Scientist

Sr. Data Scientist

ResultStack

Carolina, RI • On-site

Full-time

Re-posted 22 days ago

Job description

Must be a US Citizen or Hold a Green Card


ABOUT THE ROLE

We are looking to hire a Data Scientist who can transform the

complexity of global shipping and logistics into clear, actionable

intelligence. You'll work across operations, engineering, and leadership

to build predictive systems that optimize routes, forecast demand, and

surface insights that keep cargo moving. This is a high-impact role at the

intersection of data science, operational expertise, and emerging AI.

CORE REQUIREMENTS

This candidate will have Dashboard & BI Tooling. Being Fluent in

Tableau, Power BI, Looker, or equivalent. They will be able to model data

and present it for both technical and executive audiences.

They will have Complex Data Fluency. Being very comfortable

wrangling large, noisy datasets --- EDI records, tracking logs, port data,

weather overlays, and multi-model feeds.

They will do Predictive Modeling. Having proven experience building

ML models from messy. High-dimensional datasets (time series, sensor

data, ETA prediction, etc.).

They will be well versed in AI & Machine Learning. Having Hands-On

experience with LLM's, NLP, computer vision, or operations research

applied to real-world logistics problems.

This candidate must also be excellent in Collaboration &

Communication. They can translate model outputs into business

decisions. They will also possess strong documentation habits and

cross-functional alignment skills.

WHAT YOU'LL WORK ON

Route optimization and transit time prediction models Anomaly

detection in shipment and carrier data Real-time operational

dashboards for fleet and port performance AI-assisted demand

forecasting for freight capacity planning Cross-team data

infrastructure and model deployment support.

REQUIREMENTS

6+ Years in shipping, freight, logistics, or supply chain,

Understand how cargo and data both move.

NICE TO HAVES

Python, R, or SQL --- scripting and querying at production scale.

Software Development Principles: version control (Git), CI/CD, API

integration. Familiarity with containerization (Docker) or cloud

platform (AWS, GCP, Azure). Experience building data pipelines or ETL

workflows.