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DATA SCIENTIST

Black Financial Consult $500–$750/yr

Jun 26
Remote data-scientist Senior (5-10 yrs) Contractor
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About the role

The Data Scientist will collect, clean, and analyze structured and unstructured data to solve business problems. They will also assist in building machine learning models and creating data visualizations to support product development.

What they look for

Python R Pandas NumPy Scikit-learn SQL Power BI Tableau Machine learning Regression Classification Statistical analysis Hypothesis testing Git GitHub GitLab

Requirements

Candidates should have 2-4 years of experience and a solid understanding of statistics, probability, and data analysis. Proficiency in programming languages like Python or R and experience with SQL and data visualization tools are required.

Full description

This is a remote position.

The Data Scientist will assist in collecting, analyzing, and interpreting data to solve business problems and improve product performance. This role is ideal for early-career professionals interested in machine learning, statistical analysis, and data-driven product development.

Key Responsibilities

  • Collect, clean, and analyze structured and unstructured data.
  • Assist in building basic machine learning models and predictive algorithms.
  • Support exploratory data analysis (EDA) to generate insights.
  • Work with Product and Engineering teams to define data requirements.
  • Help visualize data insights using dashboards and reports.
  • Assist in testing and validating model performance.
  • Support experimentation and A/B testing initiatives.
  • Document analysis methods, findings, and model outputs.
  • Collaborate with data engineers to ensure data quality and availability.

Required Qualifications

  • 2-4 years of experience (internships, academic projects, or bootcamps included).
  • Understanding of statistics, probability, and data analysis.
  • Familiarity with programming for data analysis.
  • Strong analytical thinking and problem-solving skills.
  • Good communication and reporting abilities.

Technical Skills

  • Programming: Python or R (basic to intermediate)
  • Data libraries: Pandas, NumPy, Scikit-learn
  • SQL for data querying
  • Data visualization: Power BI/Tableau
  • Machine learning fundamentals (regression, classification basics)
  • Statistical analysis and hypothesis testing
  • Version control: Git / GitHub / GitLab

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