Collects, cleans, analyzes, and visualizes structured and unstructured data to solve business problems and improve product performance. Builds basic machine learning models, conducts exploratory analysis, experimentation, A/B testing, and statistical validation. Collaborates with Product, Engineering, and data engineering teams on data requirements and quality, while documenting methods, findings, and model outputs.
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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