Machine Learning / Data Mining Lead

Ultrahuman; Abu Dhabi; On-site; AED 120,000 - 200,000; Full time

Job summary

A leading company in health technology is seeking a Senior Data Scientist or ML Engineer with a strong academic background and extensive experience in machine learning. The ideal candidate will have a proven track record in delivering AI-driven solutions, guiding teams, and presenting findings to stakeholders. This role offers the opportunity to work on cutting-edge projects in a dynamic environment focused on innovation and impact.

Qualifications

• 7+ years in data science or ML engineering roles.
• 2+ years in technical leadership positions.
• Proven track record of delivering AI/ML products.

Responsibilities

• Guide engineers/researchers in ML projects.
• Deliver AI/ML-driven features to market.
• Break down complex problems and invent solutions.

Skills

Machine Learning

Data Science

Python

Problem Solving

Creativity

Education

Master's or PhD in Computer Science, Machine Learning, Data Science

Bachelor's with exceptional experience

Tools

TensorFlow

PyTorch

scikit-learn

pandas

Spark

Kafka

Job description

Educational Background: Master's or PhD in Computer Science, Machine Learning, Data Science, or related field. (Or Bachelor's with exceptional, extensive experience.) Strong theoretical foundation in machine learning, algorithms, and statistics.

Experience: 7+ years in data science or ML engineering roles, with at least 2 years in a technical leadership position guiding other engineers or researchers. Proven track record of delivering AI/ML-driven features or products to market.

Technical Mastery: Proficiency in Python and common ML libraries (TensorFlow/PyTorch, scikit-learn, pandas, etc.). Experience with data pipeline tools (Spark, Kafka, or similar) and deploying models in production environments (using cloud services or on-device inference). Solid understanding of both classical algorithms and deep learning techniques.

Domain Knowledge: Experience with time-series data or biosignals is a strong plus (e.g., physiological data, wearable data, or sensor streams). Familiarity with NLP for conversational agents or Q&A systems is beneficial.

Problem Solving & Creativity: Exceptional ability to break down complex problems and invent original solutions. Demonstrated success in tackling hard, open-ended problems with measurable impacts (e.g., improving accuracy, reducing support tickets).

Preferred Experience:

• Health Tech or Related Industries: Experience in healthtech, medtech, or fitness analytics, working on biometric algorithms, predictive health models, or digital therapeutics. Alternatively, experience in high-stakes data domains like finance or autonomous vehicles that require precision.
• Leadership & Communication: Experience presenting findings to executives or non-technical stakeholders, articulating the value of ML initiatives in terms of user impact or ROI.
• Full-Stack ML: Familiarity with the entire ML stack: from signal processing and feature engineering (especially for sensor data) to building customer-facing UI that displays ML results (collaborating with front-end teams).
• Continuous Learning: Evidence of staying current through publications, ML competitions, patents, or open-source contributions. Passion for learning and applying new technologies.

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