• Lead the development and deployment of advanced ML models and scalable systems that power critical business decisions • Develop production-ready machine learning systems with robust testing and scalable architecture • Build and improve forecasting and optimization models using XGBoost and advanced ML techniques • Design data pipelines and ML workflows that transform raw data into business intelligence • Bring research into production through experimentation, iteration, and deployment • Integrate ML systems into real business operations and user-facing tools • Drive model explainability initiatives using SHAP values and LLM-powered insights • Collaborate closely with Growth, Marketing Science, Product, and Engineering teams • Influence technical strategy while aligning ML initiatives with business impact • Mentor team members and help elevate engineering and ML standards across the organization

Role Description Workiva is seeking a Senior Applied Machine Learning Scientist to join our innovative team. In this role, you will deliver high-quality technology solutions, guide teams through complex challenges, and play a pivotal role in defining the medium-to-long-term technical strategy for impactful ML initiatives. If you excel in solving ambiguous problems, thrive in collaborative environments, and are passionate about applying machine learning to deliver business value, this opportunity is for you. Join us to tackle cutting-edge challenges and make an impact through innovative machine learning and AI applications. What You’ll Do - Own and deliver high-quality AI & ML solutions that drive business impact and align with team objectives - Develop and maintain scalable infrastructure and libraries specific to Workiva science - Collaborate with stakeholders to define project goals and solve ambiguous, open-ended problems - Lead technical initiatives, defining blueprints for complex projects involving cross-functional teams - Provide guidance on tradeoffs between thorough technical solutions and applied business value, reducing the time between POC and ROI - Mentor and guide team members, fostering a collaborative and high-performing team environment - Establish and promote best practices in MLOps, cloud infrastructure, and operational processes as it relates to the model development lifecycle - Write, review, and maintain efficient, testable, and adaptable code - Proactively optimize existing systems, reducing technical debt and ensuring scalability - Contribute to strategic planning for ML-driven initiatives and influence the team’s technical direction - Champion and evolve the culture of experimentation and measurement, ensuring sound decision making for AI and ML features in product Qualifications - Bachelor’s degree or Advanced degree (Master’s or PhD) in Computer Science, Data Science, or a related field, or equivalent experience - 2+ years of professional experience in applied machine learning or AI science Requirements - Experience designing, implementing, and deploying ML solutions - Expertise in Python, R, or similar programming languages - Experience with MLOps practices and cloud platforms (AWS, Azure, GCP) - Proficiency in experimentation and measurement - Experience leading ML modeling and solution projects, including tuning/training LLM/SLMs - Effective problem-solving skills and ability to address complex technical challenges - Excellent communication and collaboration abilities across teams - Familiarity with TensorFlow, PyTorch, or Scikit-learn - Familiarity with statistical libraries (SciPy, Statsmodels, etc.) - Knowledge of APIs and integration frameworks for scalable solutions - Proven ability to mentor junior team members and establish best practices - Experience optimizing systems for efficiency and scalability - Strong understanding of customer needs and translating them into actionable ML solutions - Excellent problem-solving skills and ability to navigate ambiguous technical challenges - Effective communication and collaboration skills with a track record of working across teams Benefits - Salary range in the US: $141,000.00 - $226,000.00 - A discretionary bonus typically paid annually - Restricted Stock Units granted at time of hire - 401(k) match and comprehensive employee benefits package

Role Description Contribute to a team responsible for developing software and machine learning products in an Agile development environment using: - Python - SQL - Relational databases including MySQL - Machine learning tools including TensorFlow, PyTorch, Scikit-learn, and XGBoost - AWS services including AWS managed Airflow and SageMaker Responsibilities include: - Modeling data using SQL - Building data warehouse and data access visualization using Looker, Grafana, and API with Python - Performing code optimization, resiliency, and parallel processing - Processing data using Big Data technologies including Spark and Snowflake - Contributing to both software engineering and machine learning sides of projects by implementing, refining, and validating machine learning algorithms for products and applications - Taking action on existing specifications of designs and developing data pipelines consisting of data ingest, data validation, data cleaning, and data monitoring - Training machine learning models, validating their accuracy, and deploying validated models into production - Researching, writing, and editing documentation and technical requirements, including evaluation plans, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations, and reports - Creating patents, including Application Programming Interfaces (APIs) and other intellectual property - Testing and evaluating solutions presented by various internal and external partners and vendors - Completing case studies, testing, and reporting - Designing proof of concept solutions and contributing to studies to support future product or application development - Collaborating with teams outside of immediate work group - Representing the work team in providing solutions to technical issues associated with assigned projects Position is eligible for 100% remote work. Qualifications - Master’s degree, or foreign equivalent, in Computer Science, Engineering, Data Science, Business Analytics, Statistics, or related technical or quantitative field - One (1) year of experience developing software and machine learning products in an Agile development environment - Experience using Python, SQL, relational databases (including MySQL, Snowflake, or Teradata) - Experience with machine learning tools: TensorFlow, PyTorch, Scikit-learn, or XGBoost - Experience using AWS services including SageMaker - Experience modeling data using SQL - Experience working with data warehouses and data access visualizations using API with Python - Experience performing code optimization - Experience processing data using Big Data technologies including Snowflake Benefits We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance, and always-on tools that are personalized to meet the needs of your reality—to help support you physically, financially, and emotionally through the big milestones and in your everyday life. Please visit the benefits summary on our careers site for more details. Company Description Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.

• Develop and improve TTS / Voice Generation models • Train, fine-tune, and evaluate speech models • Bring research ideas into production systems • Work across research, engineering, and product • Help define technical direction and ML best practices • Drive execution in a fast-changing environment • Collaborate closely with engineering, product, and business stakeholders