Job Title: Data Scientist with Reinforcement Learning
Location: Indianapolis, IN
Duration: Long Term
Job Description
We are seeking a highly skilled and experienced Data Scientist with a strong background in Reinforcement Learning to join our innovative team in Indianapolis, IN. The ideal candidate will have a robust understanding of machine learning algorithms, natural language processing (NLP), and proficiency in Python. You will be responsible for designing, developing, and implementing advanced data models and algorithms that leverage reinforcement learning techniques to solve complex problems and drive business value.
Key Responsibilities
- Design and develop reinforcement learning models and algorithms to solve complex business problems.
- Implement and optimize machine learning algorithms for various applications.
- Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
- Conduct data analysis, processing, and feature engineering to support model development.
- Evaluate and validate model performance and ensure continuous improvement.
- Communicate findings and insights to stakeholders through effective data visualization and reporting.
- Stay up-to-date with the latest advancements in machine learning, reinforcement learning, and NLP.
Key Skills
- Proficiency in Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong knowledge and hands-on experience in machine learning and reinforcement learning.
- Experience with natural language processing (NLP) techniques and tools.
- Ability to work with large datasets and perform data wrangling and preprocessing.
- Strong problem-solving skills and analytical thinking.
- Excellent communication and teamwork abilities.
Educational & Experience
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- Minimum of 6 years of professional experience in data science, with a significant focus on machine learning and reinforcement learning.
- Proven track record of deploying machine learning models in production environments.
- Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) is a plus.
- Prior experience in industries such as finance, healthcare, or technology is preferred but not mandatory.