Job description

Our client is seeking a highly skilled and experienced Senior Data Scientist specializing in Machine Learning to join their innovative analytics team in **Nashville, Tennessee, US**. This role is central to developing and deploying advanced machine learning models that drive business insights and inform strategic decision-making across the organization. You will work with complex datasets, leverage cutting-edge ML techniques, and translate analytical findings into actionable recommendations. Key responsibilities include designing, developing, and implementing machine learning algorithms for various applications, such as predictive modeling, classification, clustering, and recommendation systems. You will collaborate closely with business stakeholders to understand their needs, define analytical problems, and deliver data-driven solutions. This involves data wrangling, feature engineering, model training, evaluation, and deployment. The Senior Data Scientist will also mentor junior data scientists, contribute to the team's technical roadmap, and stay abreast of the latest advancements in data science and machine learning. The ideal candidate will possess a strong quantitative background, deep expertise in statistical modeling and machine learning frameworks, and excellent programming skills in languages like Python or R. Experience with big data technologies and cloud platforms (AWS, Azure, GCP) is highly beneficial. This is a fantastic opportunity to work on challenging problems and make a significant impact on business outcomes in **Nashville**. A proactive approach to identifying opportunities for data-driven innovation is essential. You will be expected to communicate complex technical concepts clearly and effectively to both technical and non-technical audiences. Qualifications: Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. Minimum of 5 years of experience in data science, with a strong focus on machine learning model development and deployment. Proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras). Strong understanding of statistical modeling, machine learning algorithms, and data mining techniques. Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP). Proficiency in SQL and experience with data manipulation and analysis tools. Excellent problem-solving, analytical, and critical thinking skills. Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences. Experience with data visualization tools is a plus. Ability to work independently and collaboratively in a team environment.

Requirements