TL;DR
Senior Data Scientist (AI): Designing and implementing ML models for behavior prediction, anomaly detection, and risk scoring with an accent on building end-to-end pipelines from raw behavioral signals to production-ready features. Focus on rapid prototyping, rigorous experimentation, and shipping models that scale.
Location: Work from anywhere
Company
hirify.global is the leading platform for user behavior analytics, serving multiple use cases from insider risk mitigation to business process optimization.
What you will do
- Design and implement ML models for behavior prediction, anomaly detection, and risk scoring.
- Develop and fine-tune transformer-based models.
- Optimize models for production deployment—balancing accuracy, latency, and resource efficiency.
- Build end-to-end pipelines from raw behavioral signals to production-ready features.
- Partner with product and engineering to translate business problems into data science solutions.
- Run rigorous experiments—A/B tests, causal inference, statistical validation—to measure real impact.
Requirements
- Deep hands-on expertise in Python, SQL, and ML framework (TensorFlow, PyTorch, Scikit-learn, XGBoost).
- 5+ years of experience shipping ML models to production with measurable product or business impact.
- Strong fundamentals in statistics, causal inference, and experimental design.
- Experience with transformer architectures.
- Familiarity with model optimization for production constraints.
Nice to have
- Experience with large-scale data processing (Spark, BigQuery, or similar).
- Master's degree in a quantitative discipline such as Statistics, Engineering, Computer Science, or equivalent practical experience.
Culture & Benefits
- Collaboration with a forward-thinking team where new ideas come to life, experience is valued, and talent is incubated.
- Competitive salary.
- Career growth opportunities.
- Flexible paid time off.
- Laptop reimbursement.
- Ongoing training and development opportunities.
Hiring process
- Expect up to 3 interviews.
- Director-level roles and above should expect a more thorough process, with multiple rounds of interviews.
- All roles require reference and background checks.
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