Senior Data Scientist
AngiSalary not specified
Full Time
Senior (5 to 8 years)
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Fintech, Payments, Financial ServicesIndustries
Requirements
- Degree (Masters or Ph.D. would be an advantage) in Quantitative field such as Statistics, Mathematics, Physics, Computer Science, Economics, or engineering or equivalent experience
- Minimum 8 years of professional work experience preferably in banking, payments, fintech, or a related industry
- Hands-on experience with data analytics/programming tools such as Python, R and advanced skills in querying using SQL or other query languages
- Hands-on experience working in Big Data ecosystems such as Hadoop, Spark, Hive, Kafka, GCP, AWS, and Azure. Experience with both on-prem and cloud environments is a plus
- Hands-on experience with BI tools such as Power BI and Tableau
- Proficiency in statistical techniques such as Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc
- Demonstrated experience in planning, organizing, and managing multiple and concurrent analytics projects with diverse cross-functional stakeholders
- Strong internal team and external client stakeholder management with a collaborative, diplomatic, and flexible style. Able to work effectively in a matrixed organization
- Excellent presentation and storytelling skills, including strong oral and written capabilities
- Storyboarding and data storytelling including strong Excel and PowerPoint skills
- In-market experience and/or knowledge of local language, culture as well as industry regulations
Responsibilities
- Lead, execute and deliver data science engagements for Indonesia clients
- Define detailed scope and methodology, design and create solutions, execute on frameworks leveraging appropriate tools and techniques
- Prepare and deliver presentations to clients, effectively communicating insights, recommendations, and the value of data science solutions
- Build strong relationships with Visa partners and clients, and corresponding data science/analytics teams to drive collaboration and implementation of Visa recommendations, track impact
- Ensure consistency, standards & quality control of data science work, with all project documentation up to date
- Actively seek out opportunities to innovate by using Visa’s data, client’s data and non-traditional data fit for purpose to the needs of our clients
- Enhance existing data science techniques by promoting new methodologies and best practices in the field
- Promote thought leadership in the data science domain and build intellectual property through innovation
- Effectively interact with clients and manage internal/external stakeholder communication
- Mentor, guide and supervise data scientists in the project team
Skills
Data Science
Machine Learning
Python
R
SQL
Data Analysis
Statistical Modeling
Client Management
Stakeholder Communication
Project Management
Mentoring
Thought Leadership
Visa
Global digital payment network provider
About Visa
Visa operates a global digital payment network that facilitates electronic payments for millions of people daily. The company connects consumers, businesses, financial institutions, and governments, allowing them to make transactions using Visa cards. Each time a card is used, Visa earns money through transaction, service, and data processing fees. Unlike many competitors, Visa focuses on expanding access to financial services for underserved communities and supporting local economies. The company's goal is to promote financial inclusivity and drive sustainable commerce, ensuring that more people can participate in the global economy.
San Francisco, CaliforniaHeadquarters
1958Year Founded
$55.8MTotal Funding
ANGEL_INDIVIDUALCompany Stage
Fintech, Financial ServicesIndustries
10,001+Employees
Benefits
Health Insurance.
Life Insurance.
Dental Insurance.
Disability Insurance.
Accidental Death & Dismemberment Insurance.
Risks
CBDCs could reduce reliance on Visa's payment network.
'Buy Now, Pay Later' services may decrease traditional credit card transactions.
Fintech startups offering zero-fee transactions could pressure Visa's revenue model.
Differentiation
Visa operates a global digital payment network connecting millions daily.
The company focuses on financial inclusivity and sustainability in its operations.
Visa collaborates with central banks on Central Bank Digital Currencies (CBDCs).
Upsides
Visa's partnership with fintechs enhances cross-border payment solutions.
Adoption of blockchain technology could revolutionize digital payments.
AI-driven fraud detection systems are reducing fraudulent activities.
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