Data Scientist, AI

Overview

THE ROLE

Drive business value through artificial intelligence and machine learning by developing, deploying, and optimizing AI models that tackle complex business problems and unlock insights from data. This role exists to translate business challenges into AI solutions, bringing to bear advanced analytics, machine learning, and statistical techniques to build predictive models and intelligent systems. The AI Data Scientist bridges data science theory and practical application, ensuring AI initiatives deliver measurable business impact.

HOW YOU WOULD CONTRIBUTE

• Develop and implement machine learning and AI models to address business challenges, including prediction, classification, clustering, and optimization
• Conduct exploratory data analysis to understand data patterns, identify features, and uncover insights
• Build and complete experiments to validate hypotheses and measure model performance
• Build, train, and optimize machine learning models using frameworks like TensorFlow, PyTorch, or scikit-learn
• Develop natural language processing (NLP) solutions for text analysis, sentiment analysis, and language understanding
• Implement computer vision models for image and video analysis applications
• Design and implement recommendation systems, forecasting models, and anomaly detection algorithms
• Perform feature engineering and selection to improve model accuracy and performance
• Evaluate model performance using appropriate metrics and techniques, addressing issues like overfitting and bias
• Deploy machine learning models into production environments, working with MLOps teams and infrastructure
• Monitor model performance in production and implement model retraining and updating strategies
• Collaborate with data engineers to design data pipelines that support AI/ML workflows
• Translate complex AI/ML concepts and results into clear insights for non-technical stakeholders
• Know the latest AI/ML research, techniques, and tools, applying innovations to business problems
• Document methodologies, models, and findings to ensure reproducibility and facilitate information exchange
• Make decisions on model selection, algorithm choices, evaluation metrics, and deployment strategies

Qualifications

SKILLS AND BACKGROUND REQUIRED TO BE SUCCESSFUL

• 5+ years of progressive experience in data science and machine learning; demonstrated track record of developing and deploying AI models with measurable business impact
• Machine learning and artificial intelligence algorithms and techniques
• Programming in Python and relevant ML libraries (TensorFlow, PyTorch, scikit-learn, pandas, NumPy)
• Statistical analysis and experimental design
• Data manipulation, cleaning, and preprocessing
• Model development, evaluation, and optimization
• Proven track record of developing and deploying AI/ML models that deliver business value
• Deep understanding of supervised and unsupervised learning algorithms
• Experience with model deployment and MLOps practices
• Strong mathematical and statistical foundation
• Ability to translate business problems into technical AI/ML solutions
• Deep learning architectures (CNNs, RNNs, Transformers, GANs)
• Natural language processing and large language models (LLMs)
• Computer vision techniques and frameworks
• Cloud AI/ML platforms (AWS SageMaker, Azure ML, Google Vertex AI)
• Big data technologies (Spark, Hadoop)
• Model interpretability and explainable AI (XAI)
• A/B testing and experimentation frameworks
• Domain expertise in specific industries (finance, healthcare, retail, etc.)

Education

• Minimum: Master's degree in Computer Science, Data Science, Statistics, Mathematics, Physics, or related quantitative field
• Preferred: PhD in Machine Learning, Artificial Intelligence, Computer Science, or related field; publications in AI/ML conferences or journals valuable
• Certifications: AI/ML certifications (Google Cloud ML Engineer, AWS ML Specialty, Microsoft Azure AI Engineer) valuable
• Equivalent Experience: Exceptional portfolio of AI/ML projects with 7+ years of hands-on experience and demonstrated expertise may substitute for advanced degree in rare cases

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US Benefits Statement: Herbalife offers a variety of benefits to eligible employees in the U.S. (limited to the 50 States and the District of Columbia), which includes Group Health Programs, other Voluntary Benefit Programs, and Paid Time Off. Group Health Programs include Medical, Dental, Vision, Health Savings Account (HSA), Flexible Spending Accounts (FSA), Basic Life/AD&D; Short-Term and Long-Term Disability, and an Employee Assistance Program (EAP). Other Voluntary Benefit Programs include a 401(k) plan, Wellness Incentive Program, Employee Stock Purchase Plan (ESPP), Supplemental Life/Critical Illness/Hospitalization/Accident Insurance, and Pet Insurance. Paid time off includes Company-observed U.S. Holidays, Floating Holidays, Vacation, Sick Time, a Volunteer Program, Paid Maternity and Paternity Leave, Bereavement Leave, Personal Leave and time off for voting.