Role Description This part-time remote role as a Data Analyst / Data Scientist involves working with structured and unstructured data to support decision-making and performance tracking. Day-to-day tasks include collecting, cleaning, and organizing data from various sources, building analytical models, and performing statistical analyses to identify trends, patterns, and opportunities. The role also includes preparing clear reports, dashboards, and visualizations for stakeholders, as well as explaining findings in accessible language to non-technical audiences. The Data Analyst / Data Scientist will collaborate with different teams to define analytical requirements, validate assumptions, and recommend data-driven improvements to processes and strategies. The role requires self-directed work, punctual delivery of analyses, and proactive communication in a remote environment.
Qualifications
Strong analytical skills and proven experience in data analytics to interpret complex datasets and derive actionable insights.
Solid understanding of statistics to design tests, evaluate hypotheses, and quantify uncertainty in analytical results.
Experience in data modeling, including structuring datasets, defining metrics, and building predictive or descriptive models.
Effective communication skills to translate technical findings into clear, concise recommendations for diverse stakeholders.
Proficiency with analytical tools and languages (e.g., SQL, Python or R, spreadsheets, and data visualization tools such as Power BI or Tableau).
Ability to work independently in a remote, part-time setting, manage multiple tasks, and meet deadlines with minimal supervision.
Bachelor’s degree in a quantitative field (e.g., Data Science, Statistics, Mathematics, Computer Science, Engineering, or related discipline) or equivalent practical experience.
Experience working with business, operations, or marketing teams and familiarity with KPI tracking and reporting is beneficial.
Comfort with continuous learning, adapting to new tools and methods, and contributing to a culture of innovation and improvement.

Data Analys / Data Scientist

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