Title: Data Scientist Duration: 6+ months Location: On Site- Weston, FL office Note: Only USC and GC required as this is W2 role. Skills Matrix: Have them self-rank 1-10 in terms of experience level and add # years of experience as well 1. Developing & Deploying Machine Learning Solutions: 1. Expertise in machine learning algorithms & with specific ML frameworks like TensorFlow, PyTorch, or scikit-learn: 1. Relational databases (e.g., MySQL, PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cassandra), including data modeling, query optimization, and data integration: 1. Python libraries like Pandas, NumPy, and Dask for data cleaning, transformation, and feature engineering: 1. Experience with Natural Language Processing (NLP), Large Language Models (LLMs), Natural Language Understanding (NLU), and Retrieval Augmented Generation (RAG) techniques, or other Generative AI technologies: Data Scientist Role Description: As a Lead Data Scientist, you will be a key player in driving the success of our data science initiatives, leading the execution of impactful projects, and mentoring a team of talented data scientists. You will act as a bridge between technical expertise and cross-functional teams in Sales, Marketing, Customer Success, and Product Development to identify opportunities for AI and ML to solve complex problems and drive strategic growth. This role requires a blend of technical proficiency, leadership skills, and a strong understanding of business goals. Responsibilities: • Lead and mentor a team of data scientists, providing technical guidance, fostering professional development, and promoting a collaborative work environment. • Collaborate with stakeholders across departments to understand business needs, translate them into data-driven solutions, and communicate technical concepts effectively to non-technical audiences. • Lead the design, development, and implementation of innovative data science solutions, including machine learning models, statistical analyses, and predictive algorithms. • Develop and maintain robust data pipelines for data acquisition, cleaning, transformation, and feature engineering, ensuring data quality and efficiency. • Train, validate, and deploy ML models using various algorithms, including regression, classification, clustering, time series forecasting, and reinforcement learning. • Evaluate model performance, identify opportunities for improvement, and implement optimization strategies. • Propose and implement best practices and standards for data science development, ensuring consistency, efficiency, and quality across projects. • Lead the execution of complex projects, guiding the team through all stages of the data science lifecycle. • Identify new opportunities for leveraging data science to gain a competitive advantage and drive business growth. • Contribute to the development and execution of the data science roadmap, aligning initiatives with overall business objectives and prioritizing projects for maximum impact. • Stay up to date on the latest trends and advancements in machine learning, data science, and related technologies. • Champion the adoption of data science best practices across the organization, fostering a data-driven culture. Qualifications: • Master's degree in Statistics, Computer Science, Data Science, or a related field. • 7+ years of experience in a data science role, with a proven record of accomplishment developing and deploying successful machine learning solutions. • Strong proficiency in Python, R, or other statistical programming languages. • Expertise in machine learning algorithms, including deep learning, ensemble methods, and time series analysis. • Experience with specific ML frameworks like TensorFlow, PyTorch, or scikit-learn. • Familiarity with cloud platforms such as AWS, Azure, or GCP, and experience with cloud services specifically tailored for ML development and deployment (Vertex AI, BigQuery, SageMaker, Redshift, Azure ML Studio). • Experience working with relational databases (e.g., MySQL, PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cassandra), including data modeling, query optimization, and data integration. • Strong proficiency in SQL for data querying, manipulation, and analysis, including experience with advanced SQL features like window functions and CTEs. • Experience using Python libraries like Pandas, NumPy, and Dask for data cleaning, transformation, and feature engineering. • Strong understanding of statistical concepts, hypothesis testing, and data analysis. • Experience working in an Agile environment following Scrum methodology. • Excellent communication and presentation skills, with the ability to clearly convey technical concepts to non-technical audiences. • Ability to work independently and as part of a team, contributing to a collaborative and positive work environment. • Strong problem-solving skills and a passion for data-driven decision making. • Experience working in a SaaS environment is a plus. • Demonstrated leadership skills, including the ability to mentor and guide other data scientists. • Proven ability to identify opportunities for AI/ML applications and communicate their potential value to business stakeholders. Bonus Points: • Experience with Natural Language Processing (NLP), Large Language Models (LLMs), Natural Language Understanding (NLU), and Retrieval Augmented Generation (RAG) techniques, or other Generative AI technologies.