Data Scientist, AI

Position Overview

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.

Key Responsibilities

• 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
• Stay current with 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

Required Qualifications

• 5+ years of progressive experience in data science and machine learning with a demonstrated track record of developing and deploying AI models that deliver measurable business impact
• In-depth knowledge of machine learning and artificial intelligence algorithms and techniques
• Strong programming skills in Python and experience with ML libraries such as TensorFlow, PyTorch, scikit-learn, pandas, and NumPy
• Expertise in statistical analysis, experimental design, and data preprocessing
• Proven ability in model development, evaluation, and optimization
• Solid 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
• Experience with deep learning architectures (e.g., CNNs, RNNs, Transformers, GANs)
• Knowledge of natural language processing techniques and large language models (LLMs)
• Familiarity with computer vision techniques and frameworks
• Experience with cloud AI/ML platforms (AWS SageMaker, Azure ML, Google Vertex AI)
• Proficiency in big data technologies (Spark, Hadoop)
• Understanding of model interpretability and explainable AI (XAI) principles
• Experience with A/B testing and experimentation frameworks
• Domain expertise in relevant industries such as finance, healthcare, or retail is a plus

Preferred Qualifications

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

Benefits & Perks

• Benefits: Herbalife offers a variety of benefits to eligible employees in the U.S. (limited to the 50 States and the District of Columbia), including Group Health Programs (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 (a 401(k) plan, Wellness Incentive Program, Employee Stock Purchase Plan (ESPP), Supplemental Life/Critical Illness/Hospitalization/Accident Insurance, and Pet Insurance), and Paid Time Off (Company-observed U.S. Holidays, Floating Holidays, Vacation, Sick Time, Volunteer Program, Paid Maternity and Paternity Leave, Bereavement Leave, Personal Leave, and time off for voting).