Data Scientist

? Call
8 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Remote

Tech stack

Clean Code Principles
Amazon Web Services (AWS)
Azure
Data Transformation
Data Visualization
R
Python
Machine Learning
Power BI
SQL Databases
Data Processing
Google Cloud Platform
Matplotlib
Information Technology
Data Analytics
Data Pipelines

Job description

This role is part of a talent pool for future data science projects and engagements. Selected candidates will be prioritized for upcoming opportunities involving advanced analytics, machine learning, and data-driven decision-making across industries., * Develop and deploy machine learning models and statistical solutions for complex business problems

  • Transform raw data into actionable insights using advanced data processing and visualization techniques
  • Collaborate with cross-functional teams to define data requirements and deliver impactful solutions
  • Build and manage scalable data pipelines using cloud platforms such as AWS, Azure, and Google Cloud Platform
  • Create dashboards and visualizations using Power BI and Matplotlib
  • Write clean, efficient code in Python and R for automation and analysis
  • Document methodologies and present findings clearly to technical and non-technical stakeholders

Requirements

Must-Have:

  • Strong proficiency in Python, R, and SQL for data analysis and modeling
  • Hands-on experience with Power BI for reporting and visualization
  • Experience working with AWS, Azure, and Google Cloud Platform
  • Proficiency in data visualization using Matplotlib
  • Strong analytical and problem-solving skills
  • Excellent written and verbal communication skills
  • Ability to work independently in a remote, collaborative environment

Nice-to-Have

  • Master's or PhD in Data Science, Statistics, Computer Science, or a related field
  • Experience working across multiple projects or industries
  • Experience mentoring or leading data science initiatives

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