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Data Scientist Intern Jobs in Puerto Rico (NOW HIRING)

PR · On-site

$95K - $165K/yr

You can tell which questions need a rigorous answer and which need a good-enough answer by Thursday. * 3+ years in data science, analytics engineering, or quantitative analysis with real operational ...

PR · On-site

$16.25 - $21.25/hr

Analytics Engineering Intern Position Summary At On Point Strategy , we believe that data tells a ... Data Science, Computer Science, or related fields. * Interest in data analysis, business ...

## Lead Data & Analytics Scientist ITSolicitarlocations: Santurce - Lucchettitime type: Full timeposted on: Publicado ayertime left to apply: Fecha final: 24 de julio de 2026 (Quedan 5 días para ...

## Lead Data & Analytics Scientist ITSolicitarlocations: Santurce - Lucchettitime type: Full timeposted on: Publicado ayertime left to apply: Fecha final: 24 de julio de 2026 (Quedan 5 días para ...

Intern

Guaynabo, PR

$15 - $20/hr

The Intern position is a Full time, Temporary position ... Support project teams in research, data analysis and documentation. * Contribute to the development ...

Intern

Guaynabo, PR · On-site

$15 - $20/hr

The Intern position is a Full time, Temporary position ... Support project teams in research, data analysis and documentation. * Contribute to the development ...

PR · On-site

Se solicita Profesor(a) para ofrecer cursos en el área de Inteligencia Artificial y Análisis de Datos . Requisitos Mínimos: * Bachillerato en Inteligencia Artificial, Ciencia de Datos, Ciencias de ...

Responsibilities: PR - Agricultural Intern (GUANICA / SABANA GRANDE)* Job Objectives: Give ample ... This includes planting, field maintenance, data collection, harvesting, and material handling.

PR · On-site

$11.50 - $15.50/hr

Interns will receive end-of-season reviews and each intern will be assigned a property manager, supervisor or leader as a mentor. * Candidates selected will truly want to learn and experience first ...

PR · On-site

Build software that runs on a live 1 GW production line -- internal tools, dashboards, data ... Pursuing a degree in Computer Science, Software Engineering, or a related field. * Programming ...

Human Resources Intern

Caguas, PR · On-site

$14.75 - $19.50/hr

As a world leader in life science engineering and technical solutions, MTG has the knowledge and experience to ensure compliance with pharmaceutical, biotechnology, and medical device safety and ...

PR · On-site

$13.50 - $17.75/hr

Help with employee programs, engagement, and events. * Assist with HR data, compliance, and process improvement. * Contribute to building the culture of a fast-growing manufacturer. What you bring

Data Scientist Intern information

What are the key skills and qualifications needed to thrive as a data scientist intern, and why are they important?

To thrive as a Data Scientist Intern, you generally need a strong foundation in statistics, programming (often Python or R), and data analysis, often supported by coursework in computer science or related fields. Familiarity with tools such as Jupyter Notebook, SQL, and machine learning libraries like scikit-learn or TensorFlow is typically expected. Strong problem-solving skills, curiosity, and effective communication set standout candidates apart in this role. These skills and qualities are crucial for extracting insights from data, collaborating with diverse teams, and contributing meaningful solutions to real-world problems.

What types of projects and tasks can I expect to work on as a data scientist intern?

As a Data Scientist Intern, you can expect to work on a variety of data-driven projects such as cleaning and analyzing datasets, building predictive models, and generating data visualizations to support business decisions. You'll often collaborate with other data scientists, engineers, and business teams to tackle real-world problems and may be asked to present your findings to stakeholders. These experiences are designed to help you develop technical skills, gain exposure to industry tools and methodologies, and understand how data science contributes to organizational goals.

What is a data scientist intern?

Data Scientist Interns are individuals, often students or recent graduates, who work temporarily in organizations to gain practical experience in data science. Their main responsibilities include collecting, cleaning, analyzing, and visualizing data under the guidance of experienced data scientists. Interns may also assist in building machine learning models, generating reports, and presenting insights to help solve real business problems. The internship provides valuable hands-on experience and helps interns develop technical and analytical skills necessary for a full-time data science role.

What is the difference between Data Scientist Intern vs Data Analyst Intern?

AspectData Scientist InternData Analyst Intern
Required CredentialsTypically pursuing or holding a degree in Data Science, Computer Science, or related fieldsUsually pursuing or holding a degree in Statistics, Mathematics, or related fields
Work EnvironmentInvolves building predictive models, machine learning, and advanced analyticsFocuses on data cleaning, reporting, and descriptive analytics
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprises for complex data projectsCommon in retail, marketing, and business intelligence roles across industries

While both roles involve working with data, a Data Scientist Intern typically engages in advanced analytics and machine learning projects, whereas a Data Analyst Intern focuses on data reporting and descriptive analysis. The roles differ mainly in complexity and technical skills required, but both serve as entry points into data-driven careers.

What are the most commonly searched types of Data Scientist jobs in Puerto Rico? The most popular types of Data Scientist jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Data Scientist Intern jobs? Cities in Puerto Rico with the most Data Scientist Intern job openings:
Infographic showing various Data Scientist Intern job openings in Puerto Rico as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, 2% Temporary, and 4% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

Data Scientist

Vast

PR • On-site

$95K - $165K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 4 days ago


Job description

Description:

Vast builds the operating and financial backbone for fast-growing, cash-intensive businesses, combining hands-on execution with purpose-built software, automation, and AI-enabled workflows. We provide technology-enabled shared services, financial infrastructure, and operational support to partners across the U.S. and Puerto Rico, with deep roots in route gaming and other multi-location businesses. We work execution-first, with accurate books, strong controls, and dependable processes, then build the automation and software that raise the standard for how the back office operates.


About the Role

One of the biggest partners we support is a video gaming terminal route across Illinois: machines in bars, restaurants, and truck stops, serviced by field technicians, collected by dedicated crews, supported by a call center, and run on a platform we build and maintain. Every piece of that operation throws off data, and far less of it gets used than should. This role exists to close that gap. Not by producing more charts, but by turning that data into finished work: dashboards that answer a real question, and worklists that tell a specific person what to do Monday morning.

This is not a reporting desk. If the job becomes "run this query for me," we built it wrong. It is not a research role either. Elegance is nice, but a route that runs two hours shorter is better. You will sit close to the operation and to the product and engineering teams building its platform, and your work ships into that live platform, not beside it, and the highest-value work here will be the things nobody thought to request.


What You'll Own

You will work across a deep, multi-year data estate: 250+ Illinois locations, machine and game-level performance, cash and service routing, technician dispatch, the project pipeline, call center volume, and public state reporting. Far more signal than currently gets used.

  • Finished analysis, not raw ingredients. A clear answer, the reasoning, and a recommendation someone can act on. Not a table dump.
  • Dashboards people open on purpose. Built into the system of record, in our design system, answering questions the regional directors, ops leads, and executives running the route already ask. If nobody opens it twice, it did not work.
  • Worklists, the part we care most about. Ranked, assignable lists: the specific machines, locations, or routes that need attention this week, in priority order, with the recommended move and the value of making it. Underperforming machines, wrong collection cadences, equipment to repair or replace, ground lost to nearby competition. A short list, ordered by impact, that an operator can work through.
  • Models where they earn their keep. Forecasting, route and schedule optimization, anomaly detection, siting and expected-performance models. Applied, not academic. We care about the decision it changes.

What Success Looks Like

  • First 30 days: You know the data model, the metrics, and where the bodies are buried in the data. You have been in the field at least once.
  • First 90 days: At least one dashboard and one worklist in real use, with an owner who relies on it.
  • First year: Decisions across game mix, routing, staffing, and project prioritization are measurably better because of work you initiated, including work nobody asked for.
Requirements:
  • A self-starter with an appetite for data. The best version of this hire goes looking: pulls the state's public reporting because they wondered how the operation stacks up, notices a Tuesday-evening pattern nobody asked about and chases it down, shows up to the meeting with the artifact already built. If you need a fully specified ticket before you start, this will be frustrating for both of us.
  • Fluent in the business, not just the numbers. You will talk to regional directors, technicians, collectors, and the call center, then go to the data with a better question.
  • Comfortable in a fast environment where priorities move and data is not always clean. You can tell which questions need a rigorous answer and which need a good-enough answer by Thursday.
  • 3+ years in data science, analytics engineering, or quantitative analysis with real operational impact.
  • Advanced SQL: window functions, CTEs, query tuning, and the judgment to work confidently in messy production data without hand-holding.
  • Data modeling: you can design schemas, define grain, build fact and dimension structures, and turn transactional systems into analysis-ready models.
  • Data warehousing: standing up and maintaining a warehouse or analytical layer, including ETL/ELT pipelines, incremental loads, and data quality checks.
  • Data visualization with a real point of view on chart selection, encoding, and when a number in a box beats a chart entirely.
  • Dashboarding and UI/UX design: layout, hierarchy, filter design, progressive disclosure, and mobile legibility are part of the job, not polish added at the end.
  • Experience in a modern BI or analytics platform (Tableau, Power BI, Looker, Metabase, Superset, Sigma, Quicksight, or comparable). We care that you have shipped and maintained real reporting for real users, not which tool taught you that.
  • Python or R for analysis and modeling (pandas, scikit-learn, or equivalent).
  • Forecasting and time-series analysis: seasonality, day-of-week and hour-of-day demand patterns, and the judgment to know when a trend is signal and when it is noise.
  • Geospatial analysis: clustering, drive-time and distance modeling, coverage and territory analysis. Route or network optimization experience is a strong plus, since routing is core to how the operation runs.
  • Metric definition and stewardship: you can pin down what a metric means, defend the definition, and keep it from quietly forking into three versions across the business.
  • A track record of taking an ambiguous business question and returning a defensible, actionable answer, and explaining a model to someone who will never look at the code.

Highland Holdings and its portfolio companies are equal opportunity employers. We evaluate all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.


We offer a full suite of benefits, including medical, dental, vision, 401(k) matching, and more.