MasterCard
Senior Data Scientist
MasterCard, San Francisco, CA
Our PurposeWe work 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. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.Title and SummarySenior Data ScientistMastercard 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.Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.As a Senior Data Scientist specializing with domain experience in AdTech, MarTech, or Loyalty, you will play a pivotal role in driving data-driven decision-making across various aspects of our business. RoleLeveraging your expertise in machine learning, statistical analysis, and data mining, you will be responsible for developing advanced algorithms, models, and analytics solutions to optimize advertising campaigns, enhance marketing effectiveness, and maximize customer loyalty.Collaborate with cross-functional teams to understand business objectives and translate them into data science initiatives.Design, develop, and implement machine learning algorithms and predictive models to optimize advertising targeting, campaign performance, and customer segmentation.Utilize advanced statistical techniques to analyze large datasets, extract actionable insights, and identify trends to improve marketing strategies and customer engagement.Conduct A/B testing and experimentations to measure the effectiveness of marketing campaigns and initiatives, and provide recommendations for optimization.Develop personalized recommendation systems and content personalization algorithms to enhance customer experiences and drive user engagement.Lead the development of data-driven attribution models to accurately measure the impact of marketing activities across various channels and touchpoints.Stay abreast of the latest advancements in data science, machine learning, and AI technologies, and evaluate their potential applications within the AdTech, MarTech, and Loyalty domains.Mentor and provide guidance to junior data scientists, fostering a culture of continuous learning and innovation within the team.All about youProficiency in building AI/ML models at scaleKnowledge of MLOps and model lifecycle managementHands on with python, pyspark and distributed computing concepts#AISan Francisco, CA Pay Range San Francisco, CA : 138,000.00 - 221,000.00 USD AnnualMastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.Corporate Security ResponsibilityAll 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, andComplete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary based on location, experience and other qualifications for the role and may be eligible for an annual bonus or commissions depending on the role. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance), flexible spending account and health savings account, paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave), 10 annual paid sick days, 10 or more annual paid vacation days based on level, 5 personal days, 10 annual paid U.S. observed holidays, 401k with a best-in-class company match, deferred compensation for eligible roles, fitness reimbursement or on-site fitness facilities, eligibility for tuition reimbursement, gender-inclusive benefits and many more.Pay RangesSan Francisco, California: $138,000 - $221,000 USDJob SummaryJob number: R-223376Date posted : 2024-11-14Profession: Software EngineeringEmployment type: Full time