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Role Overview
Data Scientist at Artefact, a global services company operating at the intersection of consulting, data science, AI technologies, and marketing.
Company Overview
Artefact is a global services company with 1700+ people that breaks Business and Tech silos and transforms organizations into consumer-centric leaders using digital, data and AI.
Role Purpose
To collect, prepare, analyze, and communicate data-driven insights using statistical techniques and visualization tools, working collaboratively with cross-functional teams to support evidence-based decision-making.
Key Responsibilities
Data Quality & Preparation
- Collect and extract data from various sources to prepare comprehensive datasets for analysis.
- Clean data by handling missing values, removing inconsistencies, and ensuring correct structure for further analysis.
Analysis & Insight Generation
- Analyze data using appropriate statistical techniques to uncover trends, patterns, and anomalies.
- Perform descriptive analysis and exploratory data analysis using SQL, Python, R, and statistical libraries.
- Validate and cross-check analysis results to ensure accuracy by verifying calculations and comparing findings against external or historical data.
- Investigate irregularities and catch data quality issues during analysis.
Reporting & Communication
- Create clear, concise reports and visualizations to communicate findings to internal stakeholders.
- Use Power BI and similar tools to illustrate key insights and present data in understandable formats.
- Write summaries that interpret results and highlight important conclusions.
- Explain data findings in layman's terms with excellent written and verbal communication.
Collaboration & Methodology
- Work closely with statisticians and other team members to interpret results and refine analysis approaches.
- Adjust methods based on feedback and contribute to discussions on data interpretation.
- Integrate findings into broader reports and organizational analyses.
- Partner with IT, field operations, and subject-matter experts to gather context and ensure analyses meet project needs.
- Proactively share insights and contribute to data-driven decisions.
Qualifications & Experience
- Bachelor's degree in a quantitative field such as Statistics, Data Science, Economics, Mathematics, or similar.
- Strong proficiency in SQL for database querying.
- Strong proficiency in Excel for data manipulation.
- Programming experience in Python or R for advanced analysis and automation.
- Experience with statistical libraries or packages such as pandas or R's tidyverse.
- Demonstrated ability to perform in-depth data analysis beyond visual assembly.
Skills & Competencies
- In-depth analytical mindset with demonstrated ability to write complex queries and perform statistical calculations.
- Attention to detail for interpreting data correctly and spotting outliers and errors.
- Proficiency with Power BI and similar visualization tools such as Tableau.
- Understanding of data visualization best practices and ability to communicate information effectively.
- Excellent written and verbal communication skills.
- Collaborative attitude and proactive engagement with cross-functional teams.