Senior Data Scientist - AI Products
US-CO-Englewood
Attract-careers1
Req #: 93435
Type: Fulltime-Regular
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Overview: Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow. Responsibilities: Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session. Key Responsibilities: * Partner with stakeholders to identify high-impact, feasible opportunities and demonstrate how data science can drive business outcomes. * Develop machine learning models for customer segmentation, churn prediction, user modeling, and lifetime value estimation. * Design and deploy GenAI and LLM solutions to automate complex workflows, such as transcript analysis and compliance validation. * Transform and analyze large-scale structured and unstructured data (e.g., text, images) to uncover actionable insights. * Collaborate with cross-functional teams to build and deploy scalable, cloud-based data science and GenAI solutions; provide technical mentorship. * Communicate complex models and findings to both technical and non-technical audiences via dashboards, notebooks, and presentations. Qualifications: Education and Experience: * Bachelor's or Master's degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field * 4+ years of experience in data science and applied machine learning, with a proven track record of delivering business impact from data-driven solutions Skills and Qualifications: * Strong foundation in statistical and machine learning techniques, including regression, classification, clustering, neural networks, and ensemble models. * Proficient in Python and SQL for data science workflows; skilled in building and evaluating generative AI and LLM-based solutions. * Experienced in prompt engineering, model evaluation, and deploying LLMs in production environments. * Skilled in processing unstructured data (text, images) using modern ML/DL frameworks. * Proven ability to design, run, and analyze A/B tests and controlled experiments. * Hands-on experience with AWS cloud environments and enterprise-scale ML platforms like Dataiku and Databricks. Preferred Qualifications: * Master's or PhD in a relevant quantitative domain * Experience with big data tools such as Amazon Athena, Redshift, BigQuery, Spark, or Teradata * Familiarity with MLOps practices for deploying, monitoring, and maintaining ML/GenAI systems in production * Data engineering skills for preprocessing, cleaning, and transforming large-scale datasets
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