ML Engineer Sr Consultant

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you. Job Description As a Machine Learning Engineer at the Senior Consultant / Senior Manager level, you will design and develop integrated software algorithms to structure, analyze, and leverage data in product and systems applications across both structured and unstructured environments. You will use machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and others to develop and evaluate algorithms that improve product/system performance, quality, data management, and accuracy. Rigorous validation and identification of logical flaws via sound machine learning practices are essential to support the post-deployment phase integrity and accuracy of solutions. You will translate algorithms and technical specifications into code using current programming languages and technologies. The role includes designing and implementing methods for adaptive learning (self-learning models) with controls on effectiveness, methods for explaining model decisions where necessary, model validation, and A/B testing of models. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work. Key Responsibilities Develop and program integrated software algorithms for product and systems applications in both structured and unstructured environments. Apply machine language and statistical modeling techniques to improve product/system performance, quality, data management, and accuracy. Conduct rigorous validation and identify logical flaws using sound machine learning practices. Translate algorithms and technical specifications into code using current programming languages and technologies. Design and implement methods for adaptive learning, model validation, A/B testing, and explainability of model decisions. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications Senior Consultant: 8+ years of relevant work experience with a Bachelor's Degree or at least 5 years of experience with an Advanced Degree (e.g., Master's, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience. Preferred Qualifications 9 or more years of relevant work experience with a Bachelor's Degree or 7 or more relevant years of experience with an Advanced Degree (e.g., Master's, MBA, JD, MD) or 3 or more years of experience with a PhD. Experience in developing and programming integrated software algorithms for structured and unstructured data environments. Experience in applying statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and others. Experience in rigorous validation and identification of logical flaws in machine learning solutions. Experience in translating algorithms and technical specifications into code using current programming languages and technologies. Experience in designing and implementing adaptive learning methods, model validation, and A/B testing. Experience in explaining model decisions and ensuring post-deployment integrity and accuracy. Experience in working with large datasets and modern big data and ML/AI technologies. Experience in collaborating with cross-functional teams to define requirements and ensure successful execution of machine learning initiatives. 9 or more years of relevant work experience with a Bachelor's Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD. Bachelor's Degree in Computer Science, Operations Research, Statistics or highly quantitative field (or equivalent experience) with strength in Deep Learning, Machine Learning, Data Mining, Statistical or other mathematical analysis. Experience in relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks. Ability to program in one or more scripting languages such as Perl or Python and one or more programming languages such as Java, C++ or C#. Experience with one or more common statistical tools such as SAS, R, KNIME, Matlab. Deep learning experience with TensorFlow is a plus. Information for US Applicants For roles located in the US, the estimated salary range for this position is $163,400.00 to $ 261,500.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.