Data Analyst – AI Data Collection

<p><b>Data Moderator/Analyst AI Data Collection</b></p> <p><b>Locations:</b></p> <ul> <li>(1) Las Vegas, NV</li> </ul> <p><b>4-6+ Months Contract</b></p> <p> </p> <p><b>Job Description:</b></p> <p><b>Key Responsibilities</b></p> <p>The primary duties of the Data Analyst will center around ensuring data quality and readiness for AI/ML projects:</p> <ul> <li><b>Data Sourcing and Collection:</b> <ul style="list-style-type:circle"> <li>Execute and monitor data collection processes to acquire diverse, high-volume, and high-quality data sets essential for training AI/ML models.</li> <li>Collaborate with Data Engineers and Scientists to define and implement robust data collection methodologies and pipelines.</li> </ul> </li> <li><b>Analysis and Reporting:</b> <ul style="list-style-type:circle"> <li>Conduct descriptive and diagnostic analysis on collected data to identify trends, patterns, and issues that could impact model performance (Coetzee & Goede, 2024).</li> <li>Utilize statistical methods to validate data samples and test hypotheses related to data distribution and model requirements.</li> <li>Create clear, concise reports and visualizations (e.g., dashboards) to communicate data collection progress, quality metrics, and key findings to technical and non-technical stakeholders (Meyer, 2019).</li> </ul> </li> </ul> <p><b>Required Qualifications</b></p> <p><b>Education & Experience</b></p> <ul> <li>Bachelor's degree in computer science, Data Science, Statistics, Mathematics, or a related quantitative field.</li> <li>Freshers/ Recent Graduate/Interns/1+ years of experience working as a Data Analyst or in a similar role involving extensive data manipulation and quality assurance.</li> </ul> <p><b>Soft Skills</b></p> <ul> <li><b>Analytical and Problem-Solving:</b> Proven ability to analyze complex data issues and develop practical, data-driven solutions.</li> <li><b>Communication:</b> Excellent written and verbal communication skills to articulate technical findings clearly to diverse audiences.</li> <li><b>Attention to Detail:</b> Meticulous approach to data management and quality control, which is critical for AI performance.</li> <li><b>Collaboration:</b> Ability to work effectively within a cross-functional team of Data Scientists, Engineers, and Domain Experts.</li> </ul>