Role Description The Mississippi Department of Child Protective Services seeks a senior data scientist to support a proof-of-concept demonstration using natural language processing and other machine learning methods to improve the intake process. This work is critical to demonstrate the potential of the latest technology to improve the lives of children at risk. The Senior Data Scientist will be responsible for overseeing and supporting the development, implementation, and testing of statistical models, integration of NLP, and refinement and testing of the prototype. - Evaluate algorithmic trade-offs and provide guidance to ensure the State’s objectives are satisfied. - Work closely with State stakeholders and technical team members to ensure the quality of results and that derived methods are transparent, statistically sound, relevant, and documented. Key Responsibilities - Create a Development Framework - Establish a framework for the execution of technical tasks within the proof-of-concept. - Identify critical milestones related to information, receipt of data, testing, and delivery. - Identify key risk factors and means of mitigation. - Current Processes & Technology - Participate in critical discussions involving current intake workflows and decision-making processes. - Contribute to the identification of intake process shortcomings and prioritize based on their impact on children and State resources. - Devise New Intake Approach Using New Technologies - Lead the development of a new intake process leveraging natural language processing and other machine learning algorithms. - Identify functional blocks and reconcile their contributions to solving prioritized shortcomings. - Evaluate architectural and computational implementation trade-offs for each functional block. - Evaluate trade-offs of using different data sources, including existing systems, sample data, simulated data, or other alternatives. - Document the final approach for transparency. - Design Review(s) - Create the framework for the design review process. - Lead the design review and evaluate: - The functional design with respect to resolving prioritized intake process shortcomings. - Technical, schedule, data security, and other risk factors. - Source of data and its usefulness in demonstrating the efficacy of the approach. - Proposed methods of test and demonstration. - Documentation of the process for transparency. - Implementation of Proof-of-Concept - Oversee the implementation of the prototype by conducting weekly status updates and, when appropriate, gate reviews. - Provide guidance when needed to mitigate risk and remove technical or administrative roadblocks. - Conference Room Demonstration - Provide conference room support to demonstrate how the prototype application can improve child outcomes and reduce State resources. - Capture key stakeholder comments regarding technical aspects of the application. - Roadmap - Contribute to the development of a roadmap illustrating how the developed technology could be integrated into the State’s ecosystem of technologies and processes. - Agile Development Process - Contribute to the Agile development process to ensure the success of the project. Qualifications - Bachelor’s, Master’s, or Ph.D. in computer science, mathematics, engineering, physics, or related field. - Participation in US Federal Gov’t data science programs requiring TS/SCI clearance. - Data engineering expertise with experience custom building programs processing in excess of 700 million records in less than 30 minutes. - Proven expertise working with CCWIS data attributes to predict child welfare outcomes. - Extensive knowledge of statistical algorithms, machine learning, and adaptive systems. - Prior history of designing and building machine learning algorithms from the ground up. - Experience making technical trade-offs between algorithmic approaches. - Prior success in developing optimal non-rule-based decision-making systems. - Successful history of converting social processes and human decision-making into computational models.

• Full-Cycle Ownership: Manage the entire sales process from initial technical discovery and "talking shop" with Data Science leads to final contract execution • Technical Discovery: Conduct deep-dive discovery calls to understand the customer’s specific data challenges (e.g., patient registries, clinical trial optimization, or de-identification) • Strategic Territory Planning: Build and execute a plan for your assigned territory to exceed quarterly and annual booking targets for subscriptions and services • Stakeholder Management: Orchestrate relationships across the organization, ensuring the technical "champions" stay engaged while the "economic buyers" see the ROI • CRM Discipline: Maintain meticulous records and accurate forecasts within our CRM to ensure transparency across our distributed team

Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Your Future Team You will be part of a world-class Data Science team that leverages data to drive insights about our products and customers. The Data Science team partners with Product Managers/Researchers/Data Engineers/Marketers/Privacy and Executive teams to drive and influence. They use a variety of analysis and data-science techniques to understand how Atlassian’s customers engage with our products and communications and, in doing so, identify, design, and measure the success of product investments. Responsibilities In this role, you will: - Collaborate on a variety of product and business problems with a diverse set of cross-functional partners and become a trusted strategic partner through the structure and clarity of your work. - Apply technical expertise with quantitative analysis, experimentation, and the presentation of data to develop strategies for our business and help solve the business's biggest challenges. - Focus on developing hypotheses through analytical approaches, different methodologies, frameworks, and technical approaches to test them. - Define, understand, and test opportunities to improve the products and influence roadmaps through insights and recommendations. - Partner with cross-functional teams to inform, influence, and execute strategy decisions - Identify and measure the success of product efforts through forecasting and monitoring of key product metrics to understand trends. Minimum Qualifications / Your background: - Bachelor’s degree or equivalent in a STEM field (e.g. statistics, mathematics, physics, econometrics, or computer science) - 2+ Years of Experience in Data Science or related fields - Proficiency in SQL OR another data manipulation programming language (e.g. Python, R) - Experience telling stories with data and familiarity with at least one visualization tool (e.g. Tableau, R-Shiny, Microstrategy, SAP Business Objects, Looker) - Working knowledge of basic statistical concepts (e.g. regressions, A/B tests, clustering, probability) and how to apply them to practical questions - Experience applying your analytics skills to projects which have had impact on business strategy and performance - Ability to craft analysis into well-written content Additional / Desirable Qualifications: - 4+ Years of Experience in Data Science or related fields OR 2+ Years of experience in Data Science along with a post-graduate degree or equivalent in a related field - An understanding of the SaaS business model and important metrics Qualifications Compensation At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are: Zone A: $153,000 - $199,750 Zone B: $137,700 - $179,775 Zone C: $127,800 - $166,850 This role may also be eligible for benefits, bonuses, commissions, and equity. Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. Benefits & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits. About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh.

• Analyse marketplace behaviour to uncover insights that improve supplier and buyer conversion • Interpret pharma datasets (tenders, pricing, product lists, supplier catalogues, demand signals) to identify commercial opportunities • Build dashboards that answer strategic questions rather than simply visualise data • Produce clear recommendations and commercial narratives based on your analysis • Support customer-facing teams with insight packs demonstrating platform usage and value • Diagnose conversion bottlenecks across the commercial funnel • Identify mismatches between supply and demand and propose commercial interventions • Drive alignment between Commercial and Tech on which insights matter and why • Own and manage our BI workspace (MetaBase preferred) • Ensure dashboards are accurate, intuitive, and easy for the Commercial team to self-serve • Extract data using SQL and Python when needed (not infrastructure building) • Source and integrate new pharma-related data sources to strengthen our market understanding • Enable enterprise-level decision-making by transforming commercial, marketplace, and ecosystem data into clear, decision-ready insights for the CEO and senior leadership. • Help align teams around what matters most by translating data into prioritisation signals that inform strategy, execution focus, and resource allocation. • Serve as the bridge between Tech (data pipelines) and Commercial teams • Convert technical datasets into simple, commercially meaningful insights • Highlight trends and anomalies with clear implications for growth and strategy