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Data Scientist ​

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: Master’s/PhD in Data Science, Computer Science, Statistics, or related field.
  • Experience: 3+ years in data science, with a proven track record of deploying ML models in production.
  • Technical Expertise:
    • Advanced Python (PyTorch/TensorFlow, Scikit-learn, Pandas).
    • SQL optimization for large-scale datasets (100M+ rows).
    • Cloud platforms (AWS/GCP) and distributed computing (Spark/Dask).
    • 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 and Mandarin (to align global teams).
    • Experience translating model outputs into executive-level strategy.
  • Bonus Skills:
    • 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.

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:

  1. Your resume/CV.
  2. A GitHub link or paper demonstrating a deployed ML project.
  3. A 1-page summary of how you’d approach improving our job recommendation engine.