• Lead the development and deployment of sophisticated analytics models to predict, quantify, and interpret complex data related to mortgage lending. • Utilize machine learning, statistical analysis, and other advanced techniques to improve decision-making processes, risk assessment, and customer segmentation. • Work closely with business units to identify opportunities for leveraging company data to drive business solutions. • Innovate and implement new modeling techniques and algorithms for predictive analytics and data mining. • Act as a thought leader, staying abreast of the latest industry trends and technologies in data science. • Apply advanced machine learning techniques and algorithms to analyze large and complex data sets, such as supervised and unsupervised learning, deep learning, natural language processing, computer vision, recommender systems, anomaly detection, etc. • Ensure the accuracy and integrity of data used for analysis. • Implement data collection systems and other strategies that optimize statistical efficiency and data quality. • Collaborate with data engineering teams to improve data collection, storage, processing, and security practices. • Partner with IT, software development, and business teams to translate business needs into technical specifications. • Design and build data-driven products and services that enhance the customer experience and contribute to the bottom [{not fully visible in given text}]. • Facilitate the integration of analytics and machine learning capabilities into the company’s operations and decision-making processes. • Develop and present clear, comprehensive reports and visualizations for both technical and non-technical audiences. • Communicate complex analytical results and insights in a manner that is easily understandable, facilitating informed decision-making across the company. • Provide guidance and mentorship to junior data scientists and lead project teams, ensuring the timely and successful completion of projects. • Foster a culture of innovation, continuous learning, and collaboration within the team. • Identify, track, and monitor trends and avoidable technology-related errors; work across functions to develop complex solutions, improvements, and stop-gaps. • Focus on the continual improvement of policies, procedures, and processes falling under the scope of authority. • Use expertise to resolve high level issues that cannot be solved by teammates. • Stay abreast of latest technology trends and participate in high-level decisions impacting the direction of the Information Technology function. • Partner with the DevOps team to setup scalable MLOps pipelines. • Perform other duties as assigned.

• Meet and work regularly with Leidos Business Area / Division stakeholders to work together on growing IDIQ contract vehicles, shaping strategy and opportunities, responding to RFI’s and RFP’s, gathering market intelligence, supporting all phases of the WinPlan and capture processes and to leverage IDIQ contract vehicles to meet customer mission needs and objectives. • Meet with the Leidos IDIQ and government staff, including COR and financial analyst personnel to review, analyze, and collaborate on IDIQ opportunities and customer needs. • Develop and implement solutions that align with strategic initiatives in data engineering, data science, and AI/ML. • Services include, but are not limited to, advanced analytics, model development, data governance, and the integration of innovative technologies to inform operational decisions, support military operations, and improve efficiency. • Collaborate with line management, solution architects, technical staff, functional staff, business and proposal development, capture, and other Leidos internal organizations on activities associated with IDIQ program opportunities and capture activities and reviews. • Track prior, current, prospective and future Task Orders by IDIQ. • Brief line and financial leadership on current and anticipated future IDIQ performance and opportunities. • Develop and implement IDIQ customer engagement and business growth strategy. • Attend technical conferences, demonstrations, and integration events and experiments hosted by IDIQ government and customer organizations. • Support the PMO with monitoring performance of TOs subordinate to IDIQs, ensure compliance with IDIQ requirements and PMO processes, mentor TO PM staff, and assist in resolving issues as needed. • Foster collaboration and cooperation between TO customers, TO performing staff, and IDIQ government staff as directed and needed.

• Collaborate with leaders across the organization to develop and execute on a data strategy inline with ActBlue's near and long term goals, including supporting organizational growth through acquisitions and partnerships • Foster a data centric culture by upleveling our ability to make data-informed decisions and build best in class data products that meet rigorous performance and reliability standards • Enable and advocate for AI/ML driven products and features across the ActBlue Platform through building scalable machine learning infrastructure that serves production environments and identifying new opportunities to deploy data science and analytics capacity in service of our mission • Oversee our Data Science, Data Analytics, Data Engineering, and Data Platform teams in a fast-paced, mission-driven environment • Guide the evolution of our data systems, tools, and architecture to meet the organization's needs, including data consolidation, governance frameworks, and unified data models across multiple entities • Ensure high-quality communication and a stakeholder-centric approach between our data teams and their internal customers, with an emphasis on responsiveness and partnership during high-stakes moments

Job Title: Staff Data Scientist Location: 100% remote *Telecommuting role to be performed anywhere in the U.S. Job Duties: Design and develop systems to organize and streamline the use of data in the organization. Identify relationships and trends in data, as well as any factors that could affect research results. Analyze and interpret statistical data to identify significant differences in relationships among sources of information. Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering. Develop software applications or programming to use for statistical modeling and graphic analysis. Develop and test experimental designs, sampling techniques, and analytical methods. Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighing raw data. Process large amounts of data for statistical modeling and graphic analysis, using computers. Determine whether statistical methods are appropriate, based on user needs or research questions of interest. Report results of statistical analyses, including information in the form of graphs, charts, and tables. Design research projects that apply valid scientific techniques and use information obtained from baselines or historical data to structure uncompromised and efficient analyses. Evaluate sources of information to determine any limitations, in terms of reliability or usability. Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data. Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students. Salary: $243,800 - $365,600 /year Job Requirements: Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Statistics, Biochemistry or related field and ten (10) years of experience in the job offered or related role OR Doctorate degree (U.S. or foreign equivalent) in Computer Science, Statistics, Biochemistry or related field and five (5) years of experience in the job offered or related role. Must have five (5) years of experience with: high performance computing, such as running data pipelines and/or numerical optimization on on-prem or cloud-based distributed systems; Python; and scientific programming, including code-based data analysis and optimization leveraging tools like Spark, pandas, numpy, and Mathematica. Must have three (3) years of experience with SQL and multiple databases. Must have three (3) years of databricks infrastructure management experience. Must have three (3) years of cloud data management experience, including cost accounting. Must have two (2) years of end-to-end experience building machine learning pipelines.