DATA SCIENCE STAFFING
SOLUTION
Costa Rica is a technology hub with an emerging opportunity in data science.
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
It’s easy to request a data science resource. Just call or email us or spend a minute to fill out a form. We’ll be in touch as soon!
Please be sure to check out our data science profiles below.
DATA SCIENCE STAFFING
SOLUTIONS
Costa Rica is a technology hub with an emerging opportunity in data science.
Explore the benefits of nearshoring
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
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?
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
MATH-BASED SCIENCES
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.
DATA SCIENCE PROGRAMMING
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 today’s machine learning have come into play. Programming languages like Java, C/C++, and PHP are used to develop software build around data science-related inputs and outputs
DATA VISUALIZATION
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 on a chart on a spreadsheet or presentation to developing interactive dashboards using business intelligence software like Tableau.
DATA SCIENCE GENERALISTS
Whether a business has limited data science resources or not, it usually makes sense to have a data science generalist on staff. A generalist may interact with business owners, programmers and other data science professionals. For this reason, such a person will have a broad range of data science knowledge as well as business acumen but may not possess the deep skills that data scientists with hard core machine learning skills will have. A data science generalist may also be known as a business analyst
DATA WRANGLING
The reality is that data scientists spend much of their time working with the data versus modeling. For example, data hygiene, sourcing new data and integrating it with current data, and annotating data. Skills to look out for include automation, developing workflows, APIs, and experience with multiple data formats. Data wrangling skills may overlap with traditional IT skills such as software engineers, data architects and, more broadly, data solutions
MACHINE LEARNING
Often classified as supervised or unsupervised learning, ML algorithms play a large role in data science
- linear and logistic regression
- naive Bayes classifiers
- support vector machines
- decision trees / clustering
- tensorflow platform
- ML with random forests and gradient boosting
The secret to getting things done is to act.
Dante Alighieri