Junior Data Analyst
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Role details
Tech stack
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Job description
We are seeking a detail-oriented, highly analytical Junior Data Analyst based in the United States to join our growing remote team. In this role, you will play a crucial part in monitoring dataset quality, analyzing annotator performance metrics, optimizing labeling pipelines, and delivering insights that improve our AI training data pipelines.
This is an ideal role for an early-career analyst passionate about the intersection of data, machine learning, and AI operations., * Data Quality Assurance: Audit, clean, and validate large datasets generated by our network of AI trainers and domain experts to ensure high precision and adherence to guidelines.
- Performance & Metrics Tracking: Analyze annotator accuracy, turnaround times, and throughput using SQL, Python, and BI dashboards to help optimize operations.
- Pipeline Optimization: Collaborate with cross-functional teams (Operations, AI Specialists, and Product) to identify bottlenecks in data labeling pipelines and recommend data-driven solutions.
- Reporting & Dashboards: Build, maintain, and update daily/weekly operational reports and dashboards for internal stakeholders and client leads.
- Guideline Calibration: Analyze edge cases and error patterns in dataset outputs to help refine project annotation instructions and rubrics.
Requirements
- Education: Bachelor’s degree in Data Analytics, Computer Science, Statistics, Information Systems, or a related quantitative field (or equivalent practical experience).
- Technical Skills:
- Proficiency with SQL for data querying, aggregation, and analysis.
- Practical knowledge of Python or R for data manipulation (e.g., Pandas, NumPy).
- Experience with visualization tools like Tableau, Power BI, or Looker.
- Advanced Excel / Google Sheets skills (Pivot tables, VLOOKUP/XLOOKUP, complex formulas).
- Analytical Mindset: Strong problem-solving skills with a high degree of attention to detail when working with complex datasets.
- Communication: Ability to clearly translate data findings into actionable insights for non-technical team members.
- Work Authorization: Must be legally authorized to work in the United States.
Nice-to-Haves
- Familiarity with AI/ML concepts, data annotation workflows, or RLHF (Reinforcement Learning from Human Feedback).
- Prior experience or internship experience in an operations-focused analyst role.
Benefits & conditions
What We Offer
- 100% Remote Flexibility: Work from anywhere in the US.
- Cutting-Edge Industry Exposure: Gain hands-on experience at the forefront of AI model training and evaluation.
- Growth Opportunities: Direct mentorship and opportunities to advance within a fast-growing tech environment.
- Competitive Compensation: Hourly/Salaried rate commensurate with experience.
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