Energy Jobline ZR
Associate Fraud Strategy Data Scientist (Hybrid) in San Jose
Energy Jobline ZR, San Jose, California, United States, 95199
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We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.
Job Description Note:
This is a hybrid position, so candidates must be in San Jose.
We are looking for a talented, enthusiastic, and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis, and loss mitigation. This position requires a person who has experience performing analytics, refining risk strategies, and developing predictive algorithms, preferably in the risk domain.
Key Job Functions
Design rules to detect/mitigate fraud
Develop Python scripts and models that support strategies
Investigate novel/large cases
Identify root cause
Set a strategy for different risk types
Work with product/engineering to improve control capabilities
Develop and present strategies and guide execution
Expected Outcome in 6-12 months
Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers.
Utilize data analysis to design and implement fraud strategies
Collaborate with cross-functional stakeholders, including product managers and engineering team, to deploy data‑driven fraud solutions that operate at scale and in real time for end customers.
Make business recommendations to leadership and cross‑functional teams with effective presentations of findings at multiple levels of stakeholders.
Develop dashboards and visualizations to track KPIs of fraud strategies implemented
Qualifications
Maximum 2 years of experience in risk analytics, data analysis, and data science within the relevant industry, with experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining, or related field, or equivalent practical experience.
Experience using statistics and data science to solve complex business problems.
Proficiency in SQL, Python, and Excel, including key data science libraries.
Proficiency in data visualization, including Tableau.
Experience working with large datasets.
Ability to clearly communicate complex results to technical experts, business partners, and executives, including development of dashboards and visualizations.
Comfortable with ambiguity and able to steer analytics projects toward clear business goals, testable hypotheses, and action‑oriented outcomes.
Demonstrated analytical thinking through data‑driven decisions, as well as the technical know‑how and ability to work with your team to make a big impact.
Desirable to have experience or aptitude in solving problems related to risk using data science and analytics.
Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, and fraud typologies.
Skills
Data analytics and models
Rule development
Dashboard creation
Project management
Strong communication
If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
#J-18808-Ljbffr
We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.
Job Description Note:
This is a hybrid position, so candidates must be in San Jose.
We are looking for a talented, enthusiastic, and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis, and loss mitigation. This position requires a person who has experience performing analytics, refining risk strategies, and developing predictive algorithms, preferably in the risk domain.
Key Job Functions
Design rules to detect/mitigate fraud
Develop Python scripts and models that support strategies
Investigate novel/large cases
Identify root cause
Set a strategy for different risk types
Work with product/engineering to improve control capabilities
Develop and present strategies and guide execution
Expected Outcome in 6-12 months
Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers.
Utilize data analysis to design and implement fraud strategies
Collaborate with cross-functional stakeholders, including product managers and engineering team, to deploy data‑driven fraud solutions that operate at scale and in real time for end customers.
Make business recommendations to leadership and cross‑functional teams with effective presentations of findings at multiple levels of stakeholders.
Develop dashboards and visualizations to track KPIs of fraud strategies implemented
Qualifications
Maximum 2 years of experience in risk analytics, data analysis, and data science within the relevant industry, with experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining, or related field, or equivalent practical experience.
Experience using statistics and data science to solve complex business problems.
Proficiency in SQL, Python, and Excel, including key data science libraries.
Proficiency in data visualization, including Tableau.
Experience working with large datasets.
Ability to clearly communicate complex results to technical experts, business partners, and executives, including development of dashboards and visualizations.
Comfortable with ambiguity and able to steer analytics projects toward clear business goals, testable hypotheses, and action‑oriented outcomes.
Demonstrated analytical thinking through data‑driven decisions, as well as the technical know‑how and ability to work with your team to make a big impact.
Desirable to have experience or aptitude in solving problems related to risk using data science and analytics.
Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, and fraud typologies.
Skills
Data analytics and models
Rule development
Dashboard creation
Project management
Strong communication
If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.
#J-18808-Ljbffr