Consulting Manager, Data Scientist - Visa Consulting & Analytics
- Buenos Aires, Argentina
As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.
At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.
You're an Individual. We're the team for you. Together, let's transform the way the world pays.
Visa Consulting and Analytics (VCA), the consulting arm of Visa, is a global team of industry experts in strategy, marketing, operations, risk and economics consulting, with decades of experience in the payments industry.
Our VCA teams offers:
- Consulting services customized to the needs of Visa client’s business objectives and strategy
- Business and economic insights and perspectives that impact business and investment decisions
- Self-service digital solutions Visa clients can leverage to improve performance in product, marketing and operations
- Proven data-driven marketing strategies to increase clients’ ROI
VCA team is looking for an individual to join our consulting practice and play a role developing high impact projects for Visa’s clients in South Cone Countries (Argentina, Chile, Bolivia, Paraguay, Uruguay). This potential candidate will be responsible for developing and implementing statistical modeling to address
key strategic needs for Visa’s clients including issuers, acquirers and merchants.
- Develop and deploy analytical models and techniques within the organization and VCA’s clients
including issuers, acquirers and merchants
- Work with large volumes of data; extract and manipulate large datasets using standard tools such as Hadoop Ecosystem, SAS, through scripting in Python, Spark, SQL, Java etc.
- Hands-on skills in cleaning, manipulating, analyzing, visualizing large data sets.
- Data Cleansing/Wrangling – This involve parsing and aggregating messy, incomplete, and unstructured data sources to produce data sets that can be used in analytics/predictive modeling.
- Develop and validate advance data mining tools, algorithms, and other capabilities to solve business problem. Experience doing ML using R, Python (scikit-learn, etc.) or other similar software.
- Utilize Visa's data and analytic capabilities, technology, and industry expertise to develop, standardized and implement the consulting analytical solutions.
- Identify relevant market trends by country, based on a deep analysis of payment industry Information. Interacting with several internal and external stakeholders for the strategic definition of analysis and initiatives.
- Continuously develop and present innovative ideas in order to improve current business practices within Visa.
- Perform client-specific analysis on portfolio data including proprietary information, such as customer demographics, activity, spend levels and financial information.
- Communicate complex concepts and the results of the analyses in a clear and effective
- Support transfer technical knowledge to facilitate implementation of the business
- Document all projects developed and write other documentation as needed. Identify and share best practices for key topics.
- BA/BS required; Master's degree preferred (eg: Statistics, Computer Science, Engineering or other related fields).
- 8+ years of overall experience with a preferred minimum of 5 in a banking and/or retailer
- Strong interest in the future of payments a must.
- Experience in retail banking, payments, financial services, and/or technology industries a
- Hands-on experience in advanced analytics and statistical modeling including Linear Regression, Logistic Regression, Clustering methods (e.g. K-means), Classification methods (Decision Trees/Chaid), Gradient Boosting, among others.
- Expert level knowledge of SAS (Base SAS, SAS Macro programming, SAS E. Miner, SAS E. Guide)
- Work with large volumes of data (Big Data); extract, clean and manipulate large datasets using standard tools such as Hadoop Ecosystem, Hive, Apache Spark, SAS, through scripting in Python, SQL, etc.
- Knowledge of visualization tools such as Tableau
- Transform data/ analysis to a business language
- Continuously develop and present innovative ideas based on data driven approach in order to improve current business practices within Visa
- Excellent project management, organizational and presentational skills.
- Strong teamwork, relationship management and interpersonal skills.
- Ability to multi-task various projects while meeting required deadlines.
- Results oriented
- Bilingual Spanish/English (spoken/written)
- 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, and reach with hands and arms.
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