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Senior Director of Machine Learning- Personalization Platform
2 months ago
The Data and Artificial Intelligence Platform (DAP) group is a key component of Visa’s Technology organization that provides the enabling technology and processes to handle Visa’s data assets and deliver valuable information, products, and services to customers. DAP delivers secure, high-quality, and easy-to-use Visa core data assets as a service, together with reliable and scalable data platform as a service, to enable Visa and our partners to rapidly and efficiently innovate data-driven business products and services to lead the digital payment industry.
The portfolio comprises of over 60 data products & platforms for various external clients and internal lines of business. We provide services on behalf of traditional bank customers to millions of cardholders and merchants globally. Our application development is at the forefront of technology, we are viewed as innovative leaders within our industry.
The Data Solutions & Product team is creating the next generation of scalable and responsible AI, ML and Data Innovations and products to solve client and consumer problems. We are a cross-functional team of data scientists, product managers, AI and data engineers, program managers focused on generating value for the payments ecosystem.
As a Senior Director of Machine Learning, you will drive the research, development, and implementation of our personalization platform. The role requires innovation in model optimization, system scalability, and the integration of cutting-edge AI technologies to securely redefine the customer’s personalization experience. You will build and deploy text and generation models that will have a global impact on their experiences.
Essential Functions:
- Identify opportunities to enhance personalization capabilities by diving deep into consumer and client needs.
- Develop natural language processing and personalization models that impact millions of users
- Mentor team members, share knowledge, and contribute to the technical growth of the team. Provide guidance on machine learning best practices and methodologies.
- Iterate and fine-tune algorithms and models.
- Design, implement, and maintain reliable, high-performance distributed systems.
- Act as a thought leader, staying on top of the latest advancements in Generative AI and integrating innovative technologies into our systems to maintain a competitive edge.
- Support Strategic planning, business analysis and technical knowledge of ML Engineering, tools, and data architecture solutions.
- Strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.
This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
Qualifications
Basic Qualifications:
• 12 or more years of work experience with a Bachelor’s Degree or at least 10 years of work
experience with an Advanced degree (e.g. Masters/MBA /JD/MD), or a minimum of 5 years of work experience with a PhD.
Preferred Qualifications:
• 15 or more years of experience with a Bachelor’s Degree or 12 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, or MD), PhD with 9+ years of experience.
• Expertise in multiple programming languages (e.g., Python, R, Spark).
• 5+ years’ people leadership experience of data science/AI/ML teams.
• Strengths in Deep Learning, Machine Learning, Recommendation systems, Generative models, and Statistical Analyses.
• Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn)
• Experience working with Airflow, GitHub, ML flow for building and maintaining ETL pipeline.
• Proficient in advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial, and multinomial regression, ANOVA), Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g., CART, CHAID).
• Experience working with large scale data ingestion, processing, and storage in distributed
computing environments / big data platforms (Hadoop) as well as common database systems and value stores (Parquet, Avro, HBase, etc.)
• Experience working with any of the following cloud providers: AWS, Google Cloud, and/or Azure for MLOps model development and model implementation is preferred.
Additional Information
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 protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.
U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 205,800.00 to 321,550.00 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.
