• Provide leadership to the Data Science & Analytics team and foster cross-functional collaboration (including engineering, product, etc.) to align data initiatives with broader business objectives. • Report to the Chief Technology Officer and work closely with the Director of Engineering and Sr. Director of Solutions. • Design and implement machine learning models to classify contacts, predict user engagement, and identify behavioral trends. • Develop and refine metrics to quantify spiritual growth and content effectiveness. • Analyze large datasets to extract insights that inform strategic decisions, campaign performance, and digital outreach strategies. • Design and evaluate A/B tests, multivariate experiments, and causal analyses to test hypotheses and optimize messaging, user flows, and engagement pathways. • Partner with the Director of Engineering to source, clean, and prepare structured and unstructured data for analysis and model deployment. • Communicate complex data insights to stakeholders at all levels through clear narratives and effective data visualizations, enabling data-driven decision-making across the organization. • Stay informed on trends in data science, machine learning, and AI—especially those applicable to digital engagement and nonprofit work.

At Root, we’re on a mission to improve the lives of our customers by offering better insurance solutions. We challenge ourselves to think differently in order to reimagine insurance to make it smarter, more equitable, and a better experience for all. We strive to “unbreak” the archaic insurance industry by using data and technology in innovative new ways. We believe we must be steadfast in our commitments to research, experimentation, and disciplined data-driven decision making in order to build products our customers love. The Opportunity We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry. Salary Range: $ 192,693 - $264,953 (Bonus and LTI Eligible) Root is a “work where it works best” company, meaning we will support you working in whatever location that works best for you across the US. How You Will Make an Impact Set the direction for Root’s LTV estimation framework to bring precision and rigor to Root’s critical strategic and financial decisions Define and maintain the LTV roadmap, evolving models alongside the business and delivering insights that guide both current and future decisions Lead a team of data scientists and analysts, developing talent, guiding execution, and fostering a culture of ownership, rigor, and collaboration Drive improvements in automation, maintainability, and reproducibility to support scale and cross-functional adoption of LTV tools Champion Forecast vs. Actual (FvA) analysis as a feedback loop for improving model accuracy and simulation fidelity over time. Partner closely with Marketing, Pricing, Product, and Finance to align priorities and translate modeling efforts into business impact What You Will Need to Succeed Advanced degree in a quantitative discipline (PhD preferred) and 7+ years of applying advanced quantitative techniques to problems in industry 3+ years in a leadership role, with a track record of growing talent, scaling team impact, and delivering strategic outcomes Demonstrated experience building, validating, and applying statistical machine learning methods to industry problems Proven ability to work cross-functionally to drive alignment between data science priorities and high-impact business initiatives Fluency in Python and SQL, with experience in cloud-based environments and modern data science workflows (e.g., version control, workflow automation) Excellent written and verbal communication skills, with the ability to clearly communicate with both technical and non-technical audiences Ability to consider problems from first principles, combining critical thinking with domain knowledge to navigate ambiguity Ownership mentality: takes the initiative to identify, champion, and execute on the highest impact work As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through.

IDT Corporation is a global communications company founded in 1990 and headquartered in Newark, New Jersey. We are industry leaders in prepaid communication and payment services and one of the largest international voice carriers. We are listed on the NYSE, employ over 1800 people across 20 countries, and have over $1.5 billion in revenues. IDT is not ”another big IT corporation”— we encourage and support in-house entrepreneurs in developing their ideas into business actions. We are looking for a highly technical Data Scientist to join our established Analytics department. This is a modeling-heavy role focused on building high-performance, reproducible machine learning systems that drive core business decisions. You will join an existing Analytics and Data Science department, and partner with IDT’s new AI Lab to push models into production. Responsibilites: Production-Grade Modeling: Design, develop, and maintain reproducible machine learning models for production environments. Behavioral Forecasting: Build advanced models to predict user engagement patterns, including retention and activity frequency. Optimization & Causal Inference: Develop Uplift models to measure the incremental impact of business interventions. Recommendation Systems: Improve and scale next-best-action (NBA) engines to enhance personalized user experiences. Experimental Design: Lead the statistical design and analysis of A/B testing to validate model performance and business hypotheses. Requirements Competitive salary with annual performance review. Really good hardware. An exciting and challenging job with talented people around. Continuous learning and career growth opportunities. Compensation for professional training, seminars, and conferences. Referral program – get rewarded for helping us grow the team with talented people. Company-supported English classes to enhance your professional growth. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. PLEASE SUBMIT CV IN ENGLISH. Only accepting candidates from LATAM

About Sand Sand Technologies is a fast-growing enterprise AI company that solves real-world problems for large blue-chip companies and governments worldwide. We’re pioneers of meaningful AI : our solutions go far beyond chatbots. We are using data and AI to solve the world’s biggest issues in telecommunications, sustainable water management, energy, healthcare, climate change, smart cities, and other areas that have a real impact on the world. For example, our AI systems help to manage the water supply for the entire city of London. We created the AI algorithms that enabled the 7th largest telecommunications company in the world to plan its network in 300 cities in record time. And we built a digital healthcare system that enables 30m people in a country to get world-class healthcare despite a shortage of doctors. We’ve grown our revenues by over 500% in the last 12 months while winning prestigious scientific and industry awards for our cutting-edge technology. We’re underpinned by over 300 engineers and scientists working across Africa, Europe, the UK and the US. About the role We are seeking an experienced Senior Data Scientist to join our growing data science team. As a key contributor, the Senior Data Scientist will be responsible for using their advanced data analysis and machine learning skills to solve complex business problems and drive data-driven decision-making within our organisation and those of our clients. The ideal candidate will have a strong background in statistics, machine learning and data analysis, along with a proven track record of delivering impactful, scalable solutions - with demonstrated experience getting data science solutions into production. Key responsibilities are: Conduct independent (and collaborative) research and development of data science and machine learning models; develop cutting-edge data science and machine learning models that drive business value, leveraging internal and external data sources. You are skilled in, and continue to improve upon your knowledge of decision science, communicating data, domain modelling, predictive modelling, advanced analytics, MLOps, Research and AI Ethics with the willingness to up skill others in these competencies. Collaborate with cross-functional teams: work closely with cross-functional teams to apply data science and machine learning models to business problems, ensuring that models are integrated into scalable products and services. Communicate results and impact: communicate results and impact to stakeholders, including technical and non-technical audiences. Perform cutting edge research in Physical AI, at the intersection of engineering models and AI. Mentor junior data scientists: mentor junior data scientists, fostering a culture of continuous improvement and innovation. Requirements - Essential