Job description

Our client, a leader in data-driven solutions, is seeking an accomplished Senior Data Scientist specializing in Predictive Analytics to join their innovative team. This role, based in the dynamic Denver, Colorado, US tech landscape, offers the chance to leverage complex datasets and advanced machine learning techniques to solve challenging business problems and drive strategic decision-making. You will be instrumental in building and deploying sophisticated predictive models that forecast trends, identify opportunities, and mitigate risks across various business functions. Responsibilities: Design, develop, and implement advanced statistical models and machine learning algorithms for predictive analytics. Extract, clean, and transform large, complex datasets from various sources to prepare them for analysis. Identify key business questions and translate them into data science problems. Develop and maintain data pipelines and workflows for model training and deployment. Evaluate model performance, conduct A/B testing, and iterate on models to improve accuracy and impact. Collaborate with business stakeholders, product managers, and engineers to understand needs and integrate predictive insights into products and operations. Communicate complex findings and recommendations clearly and concisely to both technical and non-technical audiences. Mentor junior data scientists and contribute to the team's technical growth. Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence. Contribute to the development of data strategy and best practices within the organization. Build and manage visualizations and dashboards to track model performance and business impact. Qualifications: Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, Economics, or a related discipline. Minimum of 6 years of professional experience in data science, with a strong focus on building and deploying predictive models. Proficiency in programming languages commonly used in data science, such as Python or R, and associated libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy). Expertise in statistical modeling, machine learning algorithms (regression, classification, clustering, time series analysis, deep learning), and experimental design. Experience with SQL and working with large-scale datasets (e.g., using Spark, Hadoop). Strong data visualization skills using tools like Matplotlib, Seaborn, Tableau, or Power BI. Excellent analytical, problem-solving, and critical thinking skills. Proven ability to communicate complex technical concepts to diverse audiences. Experience with cloud platforms (AWS, Azure, GCP) is a plus. Demonstrated experience in leading data science projects from inception to production. This is a pivotal role offering a competitive salary and the opportunity to shape impactful data-driven strategies in a hybrid work environment.

Requirements