Data Scientist

发表于 2025-06-16

最后修改 2025-08-29

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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.