Job description

Our client, a cutting-edge technology firm, is seeking an accomplished Senior Data Scientist with a specialization in Machine Learning to join their innovative team in Cincinnati, Ohio, US . This pivotal role involves designing, developing, and deploying advanced machine learning models to solve complex business problems and drive data-driven insights. You will be at the forefront of leveraging vast datasets to uncover patterns, build predictive capabilities, and optimize performance across various product lines. The ideal candidate possesses a deep theoretical understanding of ML algorithms, coupled with practical experience in implementing them in production environments. You will work collaboratively with engineers, product managers, and other data scientists, contributing to the entire data science lifecycle from data exploration and feature engineering to model deployment and monitoring. This hybrid role offers the flexibility to work from home part of the week while engaging with colleagues in the office for collaborative sessions. Key Responsibilities: Design, develop, and implement sophisticated machine learning models for prediction, classification, clustering, and anomaly detection. Conduct exploratory data analysis to identify patterns, trends, and potential insights within large datasets. Perform feature engineering and selection to optimize model performance. Evaluate and compare different modeling techniques and algorithms. Deploy machine learning models into production environments using MLOps best practices. Monitor and maintain deployed models, iterating and improving them as needed. Collaborate with engineering teams to build data pipelines and integrate models into existing systems. Communicate complex findings and model results to both technical and non-technical stakeholders through clear visualizations and presentations. Stay abreast of the latest advancements in machine learning, artificial intelligence, and data science. Mentor junior data scientists and contribute to the team's knowledge sharing initiatives. Qualifications: Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field. Minimum of 5 years of professional experience in data science, with a strong focus on machine learning. Proven experience in developing and deploying machine learning models (e.g., regression, classification, deep learning, NLP, time series forecasting). Proficiency in programming languages such as Python or R, and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Solid understanding of data structures, algorithms, and software engineering principles. Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP). Strong analytical, problem-solving, and critical-thinking skills. Excellent communication and presentation skills, with the ability to explain complex technical concepts clearly. Experience with MLOps tools and practices for model deployment and lifecycle management. Ability to work effectively in a collaborative, fast-paced environment.

Requirements