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Principal Machine Learning Scientist
2 months ago
About the Role
Talent Seed is seeking a highly skilled Principal Machine Learning Scientist to join our team in Riyadh. As a key member of our data science team, you will be responsible for leading initiatives to merge cloud infrastructure, DevOps, and machine learning to automate and deploy advanced computational processes.
Key Responsibilities
- Design and implement robust, scalable machine learning pipelines, ensuring efficient data flow from ingestion to deployment.
- Direct the design and implementation of sophisticated predictive models using Python's ecosystem, including advanced frameworks such as TensorFlow, Keras, and PyTorch.
- Engineer algorithms that are accurate and adaptable, capable of making reliable predictions across evolving datasets.
- Prototype to Production: Work closely with the engineering team to transition analytical prototypes into optimized, scalable, and fully integrated production applications.
- Utilize advanced analytical techniques to extract actionable insights from complex datasets and effectively communicate these findings to stakeholders to inform strategic decisions and promote business improvements.
- Lead efforts to explore and implement cutting-edge machine learning techniques and frameworks, enhancing our capabilities and maintaining our competitive edge.
- Manage multiple projects and mentor data scientists and machine learning scientists throughout the company.
Requirements
- Advanced degree (PhD or Masters) in a quantitative field such as Computer Science, Statistics, Mathematics, or Engineering.
- 7+ years of experience in quantitative analytics or data modeling, with a profound expertise in machine learning, predictive modeling, and algorithm development.
- Strong proficiency in Python and SQL.
- Proficiency in Python and libraries such as Pandas, NumPy, and machine learning tools (Scikit-Learn, TensorFlow, PyTorch).
- Experience working in industry and deploying Machine Learning models into production.
- Proven experience working with cross-functional and cross-cultural teams.
- Demonstrated leadership and project management experience, adept at leading cross-functional teams and mentoring junior scientists.
- Strong technical skills to improve, enhance, monitor and review machine learning models.
Preferred Qualifications
- Proficient in implementing graph analytics for fraud detection purposes.
- Anomaly detection.
- Risk scoring at onboarding, event and transaction levels.
- Device intelligence applications (fingerprinting, suspicious devices, bot detection).
- Working closely with engineering in implementing ML fraud models and processes.
- Working closely with the data science director and product in setting fraud strategy & roadmap.
- Comprehensive knowledge of AWS cloud services and architecture pertinent to data science projects.
