| Requirement for the Position :Senior ML Scientist (Pricing & Reinforcement Learning) at Remote, Remote, USA |
| Email: [email protected] |
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http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=2302713&uid= Position :Senior ML Scientist (Pricing & Reinforcement Learning) 100% remote $75/hr on C2C Below are the required skills, please check with the candidates on the below skills too and share the resume with candidates LinkedIn link attached to it. Bandits Testing: Expertise in multi-armed and contextual bandits. Optimization Techniques: Experience in Bayesian optimization, linear optimization, and pricing optimization. Neural Networks: Not a priority; focus on traditional machine learning and optimization skills. ML Optimization: Strong understanding and practical experience. Senior ML Scientist (Pricing & Reinforcement Learning) US/Canada Role Overview We seek a Senior ML Scientist to drive innovation in AI ML-based dynamic pricing algorithms and personalized offer experiences. This role will focus on designing and implementing advanced machine learning models, including reinforcement learning techniques like Contextual Bandits, Qlearning, SARSA, and more. By leveraging algorithmic expertise in classical ML and statistical methods, you will develop solutions that optimize pricing strategies, improve customer value, and drive measurable business impact. 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. Build AI-driven solutions that incorporate consumer behaviour, demand elasticity, and competitive insights to optimize revenue and conversion. Rapid ML Prototyping: Experience in quickly building, testing, and iterating on ML prototypes to validate ideas and refine algorithms. Feature Engineering: Engineer large-scale consumer behavioural 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 your models. Qualifications 8+ years in machine learning, 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 approaches for pricing optimization. Proficiency in handling tabular data, including sparsity, cardinality analysis, standardization, and encoding. Proficient in Python and SQL (including Functions, Group By, Joins, and Partitioning). Experience with ML frameworks and libraries such as scikit-learn, TensorFlow, and PyTorch Proficiency in ML optimization and in-depth understanding of Pricing optimization techniques Experience in MAB testing and optimization techniques with a focus on traditional ML Knowledge of controlled experimentation techniques, including causal A/B testing and multivariate testing Thanks & Regards, Akhil Reddy Talent Acquisition -- Keywords: artificial intelligence machine learning information technology Requirement for the Position :Senior ML Scientist (Pricing & Reinforcement Learning) [email protected] http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=2302713&uid= |
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| 02:59 AM 01-Apr-25 |