Lead integrative bioinformatic analyses of genomic data, develop bioinformatics pipelines, manage research projects, and train staff while effectively communicating findings and collaborating with diverse stakeholders to enhance pediatric rare disease...

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Data Scientist Overview Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview Are you an experienced data scientist with a passion for technological innovation, have a can-do attitude and strong sense of ownership? The Small and Medium Enterprise (SME) platform is the perfect opportunity for you to assist in the design & development of a world-class unified platform, enabling Small and Medium Enterprises globally. The SME team is looking for a Lead data scientist to own the development of machine learning models and business intelligence projects. You will also work closely with cross-functional teams, including data engineers, data analysts, and software engineers, to drive data-driven decision making throughout the organization. Key Responsibilities• Leads complex data modeling initiatives and projects to derive insights from extracted data to solve critical business questions.• Translates client/ stakeholder needs into technical analyses and/or solutions in collaboration with internal and external partners and presents findings and outcomes to clients/ stakeholders• Identify rich data sources and monitors the melding and cleaning of datasets to ensure consistency • Accountable for delivering high quality project solutions and tools within agreed upon timelines and budget parameters and conducting post- implementation reviews• Guides other to develop sophisticated multivariate models and analytic solutions (e.g., dashboards, prototypes) utilizing complex statistical and data science techniques and methods • Delegates and reviews work for junior level colleagues to ensure downstream applications and tools are not compromised or delayed• Serves as a technical coach for junior-level colleagues and develops technical talent via ongoing technical training, peer review etc. All about you • Extensive Expertise in Python or other relevant programming languages.• Strong background in statistical methods, machine learning algorithms, and predictive modelling. • Skilled in using visualization tools like Tableau, Power BI, or similar to represent complex data. • Proficiency in using big data technologies like Hadoop, Spark, or similar frameworks.• Excellent in communicating complex data insights in a clear and effective manner. • Proven ability to manage and deliver data-centric projects successfully. • Eagerness to stay abreast with the latest advancements in data science and technology. • Familiarity with cloud platforms like AWS, Azure, or Google Cloud for data processing and storage. • Knowledge of data security, privacy standards, and compliance regulations. • Working experience in Agile teams, demonstrating skills in adapting to changing requirements, fostering team collaboration, and driving efficient, iterative development processes.• Ability to work effectively in a team and with stakeholders from various backgrounds. What makes you stand out• Proven expertise in deploying machine learning models to cloud-based production environments, showcasing advanced skills in cloud technologies and the ability to scale models efficiently. • Experience with the innovative application of Generative AI in commercial settings, demonstrating the ability to leverage cutting-edge technology for practical business solutions. • Background in the financial industry, providing a deep understanding of the sector's unique data challenges and how to address them effectively. • Solid foundation in software engineering, with a focus on maintaining high code quality, effective version control, and rigorous testing practices, ensuring the development of robust and reliable software solutions. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

• Lead the full model development lifecycle for data science models (ideate, develop, deploy, and maintain) • Lead Data Science-focused projects with responsibility for planning and allocating work for any junior members on the project • Contribute to enterprise data strategy and process improvement efforts with a focus on innovation through data science and machine learning • Mentor junior members of the department to help them gain necessary senior skills to advance their careers • Work in an Agile framework and provide proactive communication and progress to management & stakeholders • Collaborate with internal and external stakeholders to manage project status and any blockers • Proactive communication and updates on progress to both management and the organization • Partner with business stakeholders to understand business problems and identify solutions for development backlog • Help develop and deliver a training curriculum for citizen data scientists across the enterprise

Role Description Snap Finance is looking to strengthen its dynamic, growing analytics department. We are seeking a dedicated Data Scientist with a passion for statistics, experimentation, and solving real-world problems. The ideal candidate is an analytically driven problem solver who can translate data into actionable business insights. In this role, you will partner with Marketing to support customer acquisition, engagement, retention, and lifetime value initiatives across multiple financial products. You'll leverage data science, experimentation, customer segmentation, personalization, and marketing measurement techniques to help drive growth and improve customer experiences. How You'll Make an Impact - Customer Insights & Personalization - Analyze customer, campaign, and behavioral data to uncover opportunities for customer acquisition, engagement, retention, and growth. - Support the development of audience segments and personalization models that enhance customer experiences across digital, paid media, SEO, email, SMS, push notifications, in-app messaging, and direct mail. - Partner with marketing teams to better understand customer behavior and identify opportunities to improve campaign performance. - Marketing Measurement & Reporting - Build and enhance attribution models that measure the incremental impact of marketing activities and customer touchpoints across channels and financial products. - Analyze cross-channel marketing performance to identify opportunities for improved targeting, personalization, and return on marketing investment. - Communicate attribution findings and performance insights in a clear, actionable manner that informs marketing strategy and business decisions. - Experimentation & Optimization - Assist in designing, executing, and analyzing experiments to measure the effectiveness of marketing campaigns, customer journeys, and personalization efforts. - Evaluate test results and provide recommendations that improve customer acquisition, engagement, retention, and marketing efficiency. - Contribute to a culture of continuous learning and optimization through data-driven decision-making. - Data Science & Analytics - Apply statistical, predictive, and analytical techniques to solve marketing and customer-focused business problems. - Build, validate, and refine models that support audience targeting, personalization, customer growth, and retention initiatives. - Work with large customer and marketing datasets to generate insights and support business decisions. - Collaboration & Stakeholder Partnership - Collaborate closely with stakeholders across Marketing, Engineering, Product, and Analytics to understand business needs and deliver meaningful insights. - Communicate analytical findings and recommendations in a way that is accessible to both technical and non-technical audiences. - Build strong working relationships and develop a deep understanding of the business, customers, and marketing goals. - AI & Innovation - Leverage AI-powered tools to improve productivity, accelerate analysis, support insight generation, and enhance marketing effectiveness. - Explore new analytical approaches and emerging technologies while applying sound business judgment and analytical rigor. - Growth & Development - We are committed to investing in your growth and development, providing opportunities to expand your technical, analytical, and business skills as you advance your career. - As our team and business continue to grow, you'll have the opportunity to take on increasingly complex challenges, broaden your impact, and help shape the future across our organization. Qualifications - 2–3 years of experience working in a data science position or performing work that aligns with the required skills in another role. - M.S. in a quantitative field such as Statistics, Econometrics, Mathematics, Physics, Computer Science, Quantitative Social Science, Quantitative Finance, or another related field. - B.S. in one of the fields described above will be considered if the candidate's skill set and experience are robust. - A skilled analyst who produces regular reporting content for key stakeholder meetings, responds to ad hoc analysis requests, and generates insightful deep dives. - Familiarity with and experience in consumer finance, digital marketing, SEO, and/or direct-to-consumer marketing. - Classification methods such as logistic regression, decision trees, KNN, and random forests. - Regression methods such as linear regression, nonlinear regression, and boosted regression trees. - Clustering methods such as k-means, hierarchical clustering, and mixture modeling. - Ability to generate robust statistical analyses, including power analysis, hypothesis testing, experimental design, hierarchical modeling, and Bayesian and frequentist methods. - Demonstrated ability to take data science projects from development to production. - Expert SQL skills and the ability to extract data from non-relational data sources. - Expertise in one or more programming languages such as Python or R. - Advanced understanding and professional experience with the following methods: What Would Make You Stand Out - Experience supporting customer growth, CRM, or lifecycle marketing initiatives, including audience segmentation, personalization, and campaign measurement across channels such as email, SMS, push notifications, paid media, or direct mail. - Hands-on experience designing and analyzing A/B tests and marketing experiments, with the ability to translate results into actionable recommendations that improve acquisition, engagement, or retention. - Familiarity with AI and machine learning applications in marketing, such as customer propensity modeling, personalization, forecasting, or using AI-powered tools to accelerate analysis and insight generation. Benefits - Generous paid time off - Competitive medical, dental & vision coverage - 401K with company match for US - Company-paid life insurance - Company-paid short-term and long-term disability - Access to mental health and wellness resources - Company-paid volunteer time to do good in your community - Legal coverage and other supplemental options - A value-based culture where growth opportunities are endless