Data Scientist I
Location
Remote
About Us
At Atomeocean, we leverage cutting-edge data science to revolutionize the job-seeking experience. Our platform harnesses AI and predictive analytics to match talent with opportunities seamlessly. We’re seeking a Data Scientist to build scalable models, uncover deep insights, and drive data-centric innovation across our product.
Job Description
You’ll architect data solutions that transform raw data into strategic assets. Partner with cross-functional teams to deploy machine learning models, design experiments, and optimize algorithms that enhance user outcomes and business growth.
Key Responsibilities
- Develop and productionize machine learning models (e.g., recommendation systems, NLP for resume/job matching, churn prediction).
- Design and analyze A/B tests and causal inference studies to measure model impact.
- Build data pipelines (Python/SQL, Airflow) to automate feature engineering and model training.
- Collaborate with engineers to implement MLOps best practices (model monitoring, versioning).
- Conduct exploratory data analysis (EDA) to identify trends, anomalies, and new feature opportunities.
- Research and prototype advanced techniques (e.g., graph algorithms, LLM fine-tuning) to solve complex problems.
- Communicate insights through dashboards (Tableau/Metabase) and technical whitepapers for stakeholders.
Core Qualifications
- Education: Bachelor’s degree in Data Science, Computer Science, Statistics, or related field.
- Experience: No prior professional work experience required.
- Technical Foundation:
- Familiarity with Python (PyTorch/TensorFlow, Scikit-learn, Pandas).
- Familiarity with SQL for querying datasets.
- Familiarity with cloud platforms (AWS/GCP) and distributed computing (Spark/Dask).
- Familiarity with experimentation frameworks (StatsModels, Bayesian inference).
- Analytical Rigor:
- Ability to balance technical depth with business pragmatism.
- Strong statistical foundation (hypothesis testing, bias-variance tradeoffs).
- Communication:
- Fluency in English.
- Ability to translate model outputs into clear summaries.
Preferred Skills
- Written and verbal communication skills in Mandarin (to align global teams).
- Deep learning (transformers, embeddings) or NLP (BERT, topic modeling).
- Feature stores (Feast) and model serving (FastAPI, Seldon).
- Publications or open-source contributions in ML/DS.
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 (O*NET-SOC 15-2051.00), 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 | Python, SQL, cloud/distributed computing, and experimentation frameworks 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.
Why Join Us?
- 🚀 Scale & Impact: Your models will directly optimize job matches for millions of users.
- 🔧 Tech Stack: Work with modern tools (MLflow, Kubeflow) and petabyte-scale data.
- 🌍 Remote Flexibility: Async-first culture with results-driven accountability.
- 📚 Learning Budget: Annual $5K for conferences (NeurIPS, ICML) or certifications.
- 🏆 Performance Rewards: Equity options and bi-annual innovation bonuses.
Ready to build the future of talent matching?
Apply with:
- Your resume/CV.
- A GitHub link or paper demonstrating a deployed ML project.
- A 1-page summary of how you’d approach improving our job recommendation engine.