Experienced Machine Learning Scientist - Remote Opportunity in Reinforcement Learning and AI-Driven Pricing Optimization

Introduction to Workwarp and the Role

Workwarp is at the forefront of innovation, leveraging cutting-edge technologies to drive business success. We are now seeking an experienced and passionate Machine Learning Scientist to join our team, working remotely from anywhere. This role offers a unique opportunity to apply your skills in machine learning, reinforcement learning, and AI-driven pricing optimization to make a significant impact on our business. As a Machine Learning Scientist at Workwarp, you will be part of a dynamic team that values innovation, collaboration, and excellence.

Job Summary

The successful candidate will have a strong background in machine learning, with a focus on reinforcement learning, recommendation systems, pricing algorithms, pattern recognition, and artificial intelligence. You will be responsible for developing and applying state-of-the-art ML models for dynamic pricing and personalized recommendations, as well as building AI-driven pricing agents that incorporate consumer behavior, demand elasticity, and competitive insights to optimize revenue and conversion.

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 AB and multivariate tests to validate the effectiveness of your models.

Essential Qualifications

To be successful in this role, you will need:

• 8+ years of experience in machine learning, with a focus on reinforcement learning, recommendation systems, pricing algorithms, pattern recognition, and artificial intelligence.
• 5+ years of experience in reinforcement learning, recommendation systems, pricing algorithms, pattern recognition, or artificial intelligence.
• Expertise in classical ML techniques, such as 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.
• Proficient 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 AB testing and multivariate testing.

Preferred Qualifications

While not essential, the following qualifications are highly desirable:

• Experience working with large-scale consumer behavioral data.
• Knowledge of cloud-based technologies, such as AWS or Azure.
• Experience with agile development methodologies and version control systems, such as Git.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.

Skills and Competencies

To succeed in this role, you will need to possess the following skills and competencies:

• Strong technical skills in machine learning, reinforcement learning, and AI-driven pricing optimization.
• Excellent problem-solving skills, with the ability to analyze complex data sets and develop creative solutions.
• Strong collaboration and communication skills, with the ability to work effectively with cross-functional teams.
• Ability to work in a fast-paced environment, with multiple priorities and deadlines.
• Strong attention to detail, with a focus on delivering high-quality results.

Career Growth Opportunities and Learning Benefits

At Workwarp, we are committed to the growth and development of our employees. As a Machine Learning Scientist, you will have access to:

• Ongoing training and development opportunities, to help you stay up-to-date with the latest technologies and techniques.
• Mentorship and coaching, to help you achieve your career goals.
• Opportunities to work on high-impact projects, with the potential to make a significant impact on the business.
• A collaborative and dynamic work environment, with a team of experienced professionals who are passionate about machine learning and AI.

Work Environment and Company Culture

At Workwarp, we value innovation, collaboration, and excellence. Our company culture is built on the following principles:

• A commitment to innovation and excellence, with a focus on delivering high-quality results.
• A collaborative and dynamic work environment, with a team of experienced professionals who are passionate about machine learning and AI.
• A focus on ongoing learning and development, with opportunities for training, mentorship, and coaching.
• A commitment to diversity and inclusion, with a focus on creating a workplace that is welcoming and inclusive to all employees.

Compensation, Perks, and Benefits

We offer a competitive compensation package, including:

• A hourly rate of $50.00 - 55.75 per hour, depending on experience.
• A comprehensive benefits package, including health, dental, and vision insurance, as well as a 401(k) plan and paid time off.
• Opportunities for professional growth and development, with a focus on ongoing learning and development.
• A dynamic and collaborative work environment, with a team of experienced professionals who are passionate about machine learning and AI.

Conclusion

If you are a motivated and experienced Machine Learning Scientist, looking for a new challenge, we encourage you to apply for this exciting opportunity. With a competitive compensation package, ongoing learning and development opportunities, and a dynamic and collaborative work environment, this role has the potential to be a rewarding and challenging career move. Don't miss out on this opportunity to join a team of experienced professionals who are passionate about machine learning and AI. Apply now and take the first step towards a rewarding new role.

Submit Your Application

Seize this opportunity to make a significant impact. Apply now and take the first step towards a rewarding new role. Please submit your application, including your resume and a cover letter, to be considered for this exciting opportunity.