Data Science Staffing Search in Nashville



Costa Rica is a technology hub with an emerging opportunity in data science.

Analytic Recruiters Nashville

We partnered with a leader in nearshoring to realize this opportunity

Large talent pool of data science professionals

Conveniently located in the same timezone as the US

Most resources are available on-demand

Resources are bilingual in English and Spanish

Resources usually cost less than comp resources in US

Data Science Search Nashville

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Please be sure to check out our data science profiles below


Data Science Staffing Search in Nashville


    Costa Rica is an emerging technology hub with a growing

    data science landscape.

    Explore the benefits of nearshoring

    newData and NOVACOMP partners

    We have partnered with a leader in nearshoring

    to realize this unique opportunity.

    Extensive talent pool of data science professionals

    Conveniently located in multiple US time zones

    Most resources are available on-demand

    Personnel are bilingual in English and Spanish

    Resources usually cost less than comparable resources in the US

    We’re proud to partner with Novacomp, a leader in technical recruiting.

    Staffing FAQs

    What is nearshoring?

    Nearshore outsourcing is a practice where businesses hire services from companies in adjacent or nearby countries.  Our nearshoring partner is based out of Costa Rica.

    Who is newData’s partner?

    novacomp is newData's nearshoring partner

    A leader in nearshoring since 1987

    What is newData’s role?

    • newData helps match the business’ job requirements with the right data science professionals offering a single point of contact
    • newData is a fully insured limited liability company that guarantees our clients’ satisfaction with all the solutions we offer

    Why nearshore data science?

    • Large pool of technical talent
    • Consultants are available on-demand
    • Bilingual in English and Spanish
    • Based out of Costa Rica on US timezone
    • Costa Rica shares many values with US
    • Lower cost than US-based outsourcing
    • Proven expertise in nearshoring

    Why is Costa Rica a talent hub?

    • Stable politically and economically
    • Ranks high for technical education
    • English is commonly spoken
    • Home to hundreds of tech companies 
    • Flourishing medical technology
    • Draws talent from Central & South America

    What is Costa Rica’s timezone?

    Costa Rica is UTC -6

      • Mountain Standard Time
      • Central Daylight Savings Time

    Staffing Roles


    The underpinning of data science is mathematics and statistics.  While most data science roles include some level of aptitude in math and stats, other roles require a graduate degree in one of these disciplines or PhD.  Other academic disciplines related to data science include Physics, Engineering, Economics, and Computer Science.


    Python, R, SQL, Scala, and Julia are just a few of the programming languages used by data scientists.  There are also programming languages like SAS and Stata that have been around long before the machine learning models of today.  Programming languages like Java, C/C++, and PHP are used to develop software around data science-related inputs and outputs.


    Data science output has many forms.  Since most people are visually oriented, it is no surprise that the visualization of data and the accompanying insights are in high demand.  The requirements range from displaying information / insights via chart, spreadsheet, or presentation to developing interactive dashboards using business intelligence software like Tableau.


    Whether a business has limited data science resources or not, it usually makes sense to have a data science generalist on staff.  A generalist (also reference to as a business analyst) interacts and liaises with business owners, programmers, and other data science professionals.  For this reason, such a person should have a broad range of data science knowledge as well as business acumen, but may not possess the deep skillsets of data scientists with extensive machine learning experience under their belt. 


    The reality is that data scientists spend much of their time working with the data versus actual modeling.  Their work typically involves data hygiene, sourcing new data, integrating it with current data, and annotating data.  Skills to look for in these resources include automation, developing workflows, APIs, and experience with multiple data formats. Data wrangling skills may overlap with traditional IT skills such as software engineering, data architecture, and more broadly, data solutioning.


    Often classified as supervised or unsupervised learning, ML algorithms play a large role in data science. Some common ML techniques include:

    • linear and logistic regression
    • naive Bayes classifiers
    • support vector machines
    • decision trees / clustering
    • kNN and K-Means
    • tensorflow platform
    • ML with random forests and gradient boosting
    AI Recruiting Nashville

    The secret to getting things done is to act.

    Dante Alighieri