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TheHiveCareers

Data Scientist

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Fully RemoteData & AIBarbados

Salary

Not listed

Posted

2h ago

Source

himalayas

Data ScienceData ScientistMachine LearningData AnalysisBusiness Intelligence

Job Type: Full-Time

Location: Barbados (Remote)

Job Summary:

A Data Scientist is responsible for analyzing complex datasets to extract insights, build predictive models, and support data-driven decision-making.

Job Description

  • Data Collection & Cleaning Gather and preprocess data from various sources to ensure accuracy.
  • Statistical Analysis & Modeling Apply machine learning algorithms and statistical techniques to uncover patterns.
  • Data Visualization & Reporting Present findings using dashboards and reports for business stakeholders.
  • Big Data Processing Work with large datasets using tools like Hadoop, Spark, and cloud platforms.
  • Collaboration & Strategy Work with cross-functional teams to align data initiatives with business goals.
  • Data Governance & Security Ensure compliance with data privacy regulations and best practices.

Required Skills

  • Proficiency in Python, R, SQL, and data visualization tools.
  • Strong understanding of machine learning, deep learning, and AI algorithms.
  • Experience with big data technologies (Hadoop, Spark, TensorFlow).
  • Knowledge of cloud computing platforms (AWS, Azure, GCP).
  • Advanced understanding of statistical analysis and predictive modeling.
  • Ability to communicate complex data insights to non-technical stakeholders.
  • Experience working within banking industry is an asset.

Educational Requirements

  • A bachelors degree in data science, computer science, mathematics, or a related field.
  • A masters degree or Ph.D. is often preferred for senior roles.
  • Certifications like Google Professional Data Scientist or AWS Certified Machine Learning Specialty can enhance qualifications.

Before you apply

  • Confirm data stack maturity (warehouse, transformation, BI tooling)
  • Ask whether the role is analyst-leaning or ML/eng-leaning
  • Check data quality ownership — who owns the source-of-truth?

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