Data Analyst I
Location
Remote
About Us
At Atomeocean, we empower jobseekers through data-driven innovation. Our platform connects talent with opportunity, and we’re seeking a curious Data Analyst to transform raw data into actionable insights that directly improve user experiences and guide strategic growth.
Job Description
You’ll be the voice of data in our product evolution. Collaborate with product, engineering, and marketing teams to uncover user behavior patterns, measure platform performance, and drive decisions that help jobseekers succeed.
Responsibilities
- Analyze user engagement, conversion funnels, and A/B test results to optimize platform features.
- Build and maintain automated dashboards (Tableau/Power BI) for real-time KPI monitoring.
- Write SQL queries to extract and transform data from relational databases.
- Perform ad-hoc analyses to answer critical business questions (e.g., "Which features boost user retention?").
- Clean and validate data to ensure reporting accuracy.
- Partner with engineers to define data tracking requirements for new features.
- Present findings to stakeholders through clear visualizations and actionable recommendations.
- Identify trends and anomalies to proactively surface growth opportunities or risks.
Qualifications
- Education: Bachelor’s degree in Data Science, Statistics, Economics, or a quantitative field.
- Experience: No prior professional work experience required.
- Technical Skills:
- Familiarity with SQL (joins, aggregations).
- Familiarity with Python/R for data manipulation (Pandas, NumPy) and basic statistical analysis.
- Familiarity with BI tools (Tableau, Power BI, or Looker).
- Basic understanding of experimental design (A/B testing principles).
- Analytical Mindset:
- Ability to translate vague questions into structured analysis.
- Keen eye for spotting data inconsistencies.
- Communication:
- Fluency in English.
- Skill in simplifying technical insights for non-technical audiences.
Preferred Skills
- Written and verbal communication skills in Mandarin (to collaborate with global teams).
- Experience with big data tools (Spark, BigQuery).
- Knowledge of web analytics (Google Analytics, Mixpanel).
- Basic machine learning concepts (regression, clustering).
Preferred But Not Required
All preferred qualifications are optional and are not minimum requirements for the position.
These preferred skills do not increase the complexity of the offered position and do not elevate the wage level.
The entry-level employee will work under close supervision, and all advanced tasks will be assigned only to senior staff.
Wage Level Justification
This posting is classified using the worksheet method from the DOL's 2009 Prevailing Wage Determination Policy Guidance (see Wage Level Determination). Baseline occupation: Data Scientists (ONET-SOC 15-2051.00), the ONET classification covering Data Analyst roles; Job Zone 4 — experience range over 2 and up to 4 years; usual education: Bachelor's degree.
This posting is the Level I baseline. Every determination starts at Level I, and none of the four scored factors adds a point here:
| Worksheet step | This posting | Points |
|---|---|---|
| Step 2 Experience | No prior professional work experience required — at or below the start of the Job Zone 4 range | +0 |
| Step 3 Education | Bachelor's degree, the usual education for the occupation | +0 |
| Step 4 Special Skills | SQL, Python/R, BI tools, and experimental design are covered by the occupation's O*NET Tasks and Work Activities baseline; Mandarin is preferred but not required, so no foreign-language point applies | +0 |
| Step 5 Supervisory Duties | None | +0 |
Starting at Level I (1) + 0 points = Level I.
Additional Information
- 💻 Fully remote – Work from anywhere with flexible hours.
- 📈 Impact-Driven – Your insights directly shape a product helping millions find jobs.
- 🌱 Growth Support – Annual stipend for courses/conferences (e.g., Coursera, DataCamp).
- ⚕️ Comprehensive Benefits – Health insurance, paid leave, and performance bonuses.
Ready to decode data into human impact?
Submit your resume and a case study showcasing how your analysis drove business decisions!