• Partnering with teams across Canva to influence strategic decisions through data. • Designing and analysing A/B tests and other experiments that drive product and business outcomes. • Building data models, dashboards, and tooling that help teams scale insights. • Defining and forecasting key metrics to track progress and surface opportunities. • Communicating findings clearly to a wide range of technical and non-technical audiences. • Uplifting the broader data community through mentorship, best practices, and collaboration.

• 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