Senior Data Scientist (Python, Spark, SQL, Hadoop, XGBoost, Transformers, RNN, LSTM, Decision Tree, Regression)

With data being the fuel that drives our future - our strategies policies and business successes around data will define our future growth prospects. Unlocking the value available through the innovative use of data on behalf of consumers businesses and communities is key to our future. With our ongoing commitment to Visas Data Values and the responsible use of data we at Visa have a bold vision to continue to grow and accelerate our data-related businesses and capabilities. 

Led by Visas Chief Data Officer the Global Data Office coordinates high-impact complex company-wide projects related to data business strategy critical investments policy development and marketplace execution. Working closely with Visas Chief Privacy Officer the Technology organization the wider data community and the full set of Visas global lines of business the Global Data Office is evolving Visas data-related work with momentum and enthusiasm. Driven by its commitment to trusted use of data Visa is seeking enthusiastic leaders who are change-agents and passionate about the future of data around the world. 

The AI/ML Products and Platforms team under the Global Data Office 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. We are dreaming of the next generation of AI features and products.

This position is in the Data Science vertical under the AI/ML Products and Platforms this role you will be an individual contributing to develop AI driven products and services specifically focused on development of models and signals to deliver personalized customer experiences. These personalization models and signals will power Data Tokens and many other personalization-related use cases. The ultimate goal is to better link consumers with products and services with benefits for every party in the payments ecosystem (consumers businesses). 

Responsibilities include: 

Solve complex problems for our clients and Visa using appropriate data AI/ML models and data science techniques as part of a Center of Excellence (CoE) team. Create frameworks and assets which can be leveraged by global and regional data science teams across Visa to address business problems.

Technical Leadership:

• Develop and Execute data science capabilities useful for Visa and its clients
• Design and develop large-scale data science systems
• Foster innovation and experimentation within the team

Data Science:

• Apply advanced data science techniques and models to drive business impact
• Stay up-to-date with industry trends and emerging technologies
• Develop and maintain expertise in multiple programming languages and data science tools

Collaboration:

• Work closely with cross-functional teams to integrate data science capabilities
• Communicate complex technical concepts and results to stakeholders.
• Influence business decisions with data-driven insights

Strategy:

• Execute data science strategy aligned with business goals
• Identify opportunities for data science to drive business impact

Communication:

• Communicate complex technical concepts and results to stakeholders
• Present data science capabilities and results to senior leadership and business partners

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. 

Qualifications :

Basic Qualifications:
5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters MBA JD MD) or 0 years of work experience with a PhD

Preferred Qualifications:
6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters MBA JD MD) or up to 3 years of relevant experience with a PhD
4 years of work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters MBA JD MD) or 0 years of work experience with a PhD degree
Preferred Qualifications
6-8 years of work experience with a Bachelors Degree or 4-6 years of work experience with an
Advanced Degree (e.g. Masters MBA JD MD) or 3 years of experience with a PhD
4 years experience in data-based decision-making or quantitative analysis
Masters degree in Statistics Operations Research Applied Mathematics Economics Data Science Business Analytics Computer Science or a related technical field
Develop and maintain expertise in multiple programming languages (e.g. Python R Spark)
Stay current with industry trends and advancements in data science tools and technologies (e.g.   TensorFlow PyTorch scikit-learn)
Extracting and aggregating data from large data sets using SQL/Hive or Spark
Analyzing large data sets using programming languages such as Python R SQL and/or Spark
Generating and visualizing data-based insights in software such as Tableau
Communicating evidence based insights and conveying relevant recommendations
Leading and coordinating work in Office software
Building predictive and descriptive statistical models using machine learning tool kit Jupiter notebooks Python and/or SAS
Data mining and statistical modeling (e.g. regression modeling clustering techniques decision trees etc.)
Previous exposure to financial services credit cards or merchant analytics is a plus but not required
Running projects from scoping to delivery and engaging with internal/external partners

Additional Information :

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.

Remote Work :

No

Employment Type :

Full-time