• Develop and productionize statistical machine learning models for probabilistic country attribution based on browsing patterns and behavioral signals • Design and refine predictive models and statistical algorithms to improve accuracy and reliability of behavioral calculations • Work with petabyte-scale datasets to extract, clean, and analyze large volumes of behavioral data • Build scalable data pipelines and modeling workflows using Python and SQL • Collaborate with engineering and product teams to integrate models into production services • Create clear visualizations and reports to communicate model performance and insights • Own end-to-end algorithm development and model lifecycle management • Mentor junior team members as the role evolves into Data Scientist Lead

• Serve as lead when working collaboratively with teams of health services researchers and business analysts to draw insight and intelligence from large administrative claims datasets, electronic medical records and various healthcare registry datasets; • Identify and develop solutions that can be implemented to key strategic business problems using high-level modeling and statistical analyses techniques; • Utilize SQL to perform advanced-level data extraction, transformation and data management; fully document and manage library of source code and algorithms for future use; • Identify, develop and test hypotheses in support of research and product offerings, and communicate findings in a clear, precise, and actionable manner to our clients; • Respond to and lead highly complex operational data requests and create ad-hoc queries to support research projects; • Serve as lead when working closely with Inovalon’s Enterprise Data Management, Data Integration, MORE2 Registry®, and iPORT+™ teams to identify, understand, and resolve data issues and improve the efficiency, productivity and scalability of Avalere and Inovalon Product and production data processes; • Troubleshoot complex production-related issues and coordinate successful resolution; • Assist with the evaluation of data analytic vendors and tools; • Maintain compliance with Inovalon’s policies, procedures and mission statement; • Adhere to all confidentiality and HIPAA requirements as outlined within Inovalon’s Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the undertaking of the position; • Fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success of the Company; • Uphold responsibilities relative to the separation of duties for applicable processes and procedures within your job function; • We reserve the right to change this job description from time to time as business needs dictate and will provide notice of such.

Role Description We are seeking an experienced Data Scientist III to join our team. As a Data Scientist III, you will be responsible for the full data science lifecycle, from data acquisition and wrangling to model building, deployment, and monitoring. You will focus on utilizing advanced techniques in Python programming, machine learning (ML), deep learning (DL), and generative AI to solve complex problems and develop impactful solutions for our customers. This role requires a strong blend of technical expertise, analytical thinking, and problem-solving skills. You will work collaboratively with cross-functional teams, including engineers, product managers, and data analysts, to ensure data-driven decision making across the organization. Responsibilities - Design, develop, and implement machine learning and deep learning models for various applications, such as customer churn prediction, recommendation systems, anomaly detection, and natural language processing. - Leverage Python programming and its relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn) to build and iterate on models. - Explore and experiment with cutting-edge techniques in generative AI to create innovative solutions for government and citizen engagement. - Collaborate with product managers, engineers, and stakeholders to understand business requirements and translate them into data-driven solutions. - Collaborate with software and data engineers to ensure seamless integration of models into Granicus products and platforms. - Perform data analysis, cleansing, and feature engineering to prepare high-quality data for model training. - Develop and maintain robust pipelines for data ingestion, transformation, and model training. - Continuously monitor and evaluate model performance, identify areas for improvement, and iterate on models. - Communicate complex technical concepts to stakeholders in a clear and concise manner. - Contribute to the development of best practices, tools, and frameworks for data science and machine learning initiatives. - Stay up to date on the latest advancements in data science and AI research. Qualifications - Bachelor’s or Master’s degree in computer science, Statistics, Mathematics, or a related quantitative field. - 5+ years of experience in data science, machine learning, or a relevant field. - Proficiency in Python programming and familiarity with relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn). - Strong understanding of machine learning and deep learning algorithms and techniques. - Experience with generative AI models, such as text generation, image generation, or other creative applications. - Proficiency in data manipulation, analysis, and visualization using Python libraries (e.g., Pandas, NumPy, Matplotlib). - Experience with cloud platforms and big data technologies (e.g., AWS). - Excellent problem-solving, critical thinking, and analytical skills. - Strong communication and collaboration skills, with the ability to explain complex technical concepts to diverse audiences. Requirements - Knowledge of graph neural networks, reinforcement learning, or other advanced machine learning techniques. - Familiarity with agile software development methodologies and DevOps practices. - Experience with containerization technologies (e.g., Docker, Kubernetes). - Contributions to open-source projects or published research in machine learning, deep learning, or generative AI. - Experience with generative AI models (GANs, VAEs, etc.). - Experience working with government or public sector data. - Experience with data visualization tools (Tableau, Power BI). Benefits - Don’t have all the skills/experience mentioned above? At Granicus, we are trying to build diverse, inclusive teams. - We do not have degree requirements for most of our roles. - If you don’t meet every requirement above but are excited to learn more, we encourage you to apply. - We might just be able to find another role that could be a perfect fit!

• Research, develop, and ship sophisticated pricing models (e.g. Tree-based, Gradient-based, Deep Learning, ensemble methods) to improve valuation accuracy for high-value assets. • Identify new data signals — emanating from data such as auction results to social sentiment — and validate their predictive power through rigorous backtesting and experimentation. • Partner with the Product Engineering team to refine our Risk & Underwriting models, balancing the goal of maximizing cash advances with the need to maintain a balanced lending portfolio. • Collaborate with the Expert Pricing team and domain experts to encode market nuances into automated features and inferences, ensuring our models respect the qualitative factors collectors care about. • Define, monitor, and lift model performance metrics and communicate the "why" behind price coverage, movements, and freshness toward becoming the ultimate liquidity platform.