Data Scientist

<p><strong>About us:</strong></p> <p>Artefact is a global services company that sits at the intersection of consulting, data science, AI technologies and marketing. Our 1700+ people break Business and Tech silos and transform organizations into consumer-centric leaders using digital, data and AI.</p> <p><strong>Key Responsibilities:</strong></p> <ul> <li>Data Quality Analysis & Remediation: Collect, extract, and clean data from various sources to prepare comprehensive datasets for analysis This includes handling missing data, removing inconsistencies, and ensuring the data is structured correctly for further analysis.</li> <li>Analyze data using appropriate statistical techniques and tools to uncover trends, patterns, and anomalies in the information. This could involve anything from simple descriptive analysis to more complex exploratory data analysis</li> <li>Validate and cross-check analysis results to ensure accuracy. This involves verifying calculations, comparing findings against external or historical data for consistency, and investigating any irregularities in the results. Data Analysts are expected to be vigilant about data quality during analysis, catching any issues that might have passed initial data processing.</li> <li>Create clear, concise reports and visualizations to communicate findings. While the focus is on analysis rather than just creating dashboards, analysts will use tools like <strong>Power BI</strong> to illustrate key insights. They should present data in an understandable way for internal stakeholders, writing summaries that interpret the numbers and highlight important conclusions.</li> <li>Work closely with statisticians and other team members to interpret results and refine analysis approaches. This collaborative approach ensures that the analysis aligns with methodological standards and project goals. Analysts may adjust their methods based on feedback, contribute to discussions on what the data means, and help integrate their findings into broader census reports.</li> </ul> <p><strong>Key Qualifications:</strong></p> <ul> <li>Bachelor’s degree in a quantitative field such as Statistics, Data Science, Economics, Mathematics, or similar. This educational background provides a solid foundation in data analysis techniques and statistical reasoning.</li> <li>Strong proficiency in data analysis tools and languages, particularly <strong>SQL</strong> for database querying, Excel for data manipulation, and programming in Python or R for more advanced analysis and automation. Experience with statistical libraries or packages (e.g., pandas, R’s tidyverse) is highly valuable.</li> <li>Demonstrated ability to perform in-depth data analysis and not just generate visuals. We need a