Experience:

• Machine learning: 8 years (Required)
• Python: 4 years (Required)
• Reinforcement learning: 5 years (Required)
• Machine learning libraries: 4 years (Required)
• SQL: 3 years (Required

RESPONSIBILITIES AND DUTIES:

· 8+ years in machine learning, including 5+ years in reinforcement learning, recommendation systems, pricing algorithms, pattern recognition, or artificial intelligence.
· Expertise in classical ML techniques (e.g., Classification, Clustering, Regression) using algorithms like XGBoost, Random Forest, SVM, and KMeans, with hands-on experience in RL methods such as Contextual Bandits, Q-learning, SARSA, and Bayesian approaches for pricing optimization.
· Proficiency in handling tabular data, including sparsity, cardinality analysis, standardization, and encoding.
· Strong coding skills in Python and SQL (including Window Functions, Group By, Joins, and Partitioning).
· Experience with ML frameworks and libraries such as scikit-learn, TensorFlow, and PyTorch.
· Knowledge of controlled experimentation techniques, including causal A/B testing and multivariate testing.

KEY RESPONSIBILITIES

· Algorithm Development: Conceptualize, design, and implement state-of-the-art ML models for dynamic pricing and personalized recommendations.
· Reinforcement Learning Expertise: Develop and apply RL techniques, including Contextual Bandits, Q-learning, SARSA, and concepts like Thompson Sampling and Bayesian Optimization, to solve pricing and optimization challenges.
· AI Agents for Pricing: Build AI-driven pricing agents that incorporate consumer behavior, demand elasticity, and competitive insights to optimize revenue and conversion.
· Rapid ML Prototyping: Quickly build, test, and iterate on ML prototypes to validate ideas and refine algorithms.
· Feature Engineering: Engineer large-scale consumer behavioral feature stores to support ML models, ensuring scalability and performance.
· Cross-Functional Collaboration: Work closely with Marketing, Product, and Sales teams to ensure solutions align with strategic objectives and deliver measurable impact.
· Controlled Experiments: Design, analyze, and troubleshoot A/B and multivariate tests to validate the effectiveness of models.
Job Types: Full-time, Contract
Pay: $70.00 - $73.00 per hour

Schedule:

• 8 hour shift
• Day shift
• Monday to Friday

Experience:

• Machine learning: 8 years (Required)
• Python: 4 years (Required)
• Reinforcement learning: 5 years (Required)
• Machine learning libraries: 4 years (Required)
• SQL: 3 years (Required)

Ability to Commute:

• San Jose, CA 95110 (Required)

Ability to Relocate:

• San Jose, CA 95110: Relocate before starting work (Required)

Work Location: In perso