Data Scientist / ML Engineer at Franklin Templeton designing and productionizing machine learning systems for business solutions. Collaborating with teams to deliver scalable and reliable ML solutions.
About the role
- Data Scientist II developing machine learning models to improve fraud detection at USAA. Collaborating with analytics community and working with structured/unstructured data for analytical solutions.
Responsibilities
- Responsible for the development of machine learning models that improve fraud detection and prevention
- Develop and continuously update internal fraud models
- Work with Strategies and Model Management teams to understand and plan model needs
- Drive continuous innovation in modeling efforts
- Collaborate with the broader analytics community
- Capture, interpret, and manipulate structured/unstructured data for analytical solutions
- Select appropriate modeling technique and/or technology
- Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework
- Compose technical documents for knowledge persistence and risk management
- Consult with Data Engineering, IT, and other internal partners to deploy solutions aligned with the customer’s vision
Requirements
- Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience may be substituted in lieu of degree
- 2 years of experience in predictive analytics or data analysis OR Advanced Degree (e.g., Master’s, PhD) in relevant field
- Experience in training and validating statistical, physical, machine learning, and other sophisticated analytics models
- Experience in one or more multifaceted scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models
- Ability to write code that is easy to follow, well detailed, and commented where vital to explain logic
- Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
- Experience in working with structured, semi-structured, and unstructured data files
- Familiarity with performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics
- Experience with classical supervised modeling for prediction such as linear/logistic regression, decision trees, etc.
- Experience with concepts associated with unsupervised modeling such as k-means clustering, neighbors algorithms, etc.
- Ability to communicate analytical and modeling results to non-technical business partners
Benefits
- comprehensive medical, dental and vision plans
- 401(k)
- pension
- life insurance
- parental benefits
- adoption assistance
- paid time off program with paid holidays plus 16 paid volunteer hours
- various wellness programs
- career path planning and continuing education
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Scientist leading complex analytics projects to drive data - informed business decisions. Collaborating with senior leadership at Vanguard to enhance analytical capabilities.
Data Scientist creating machine learning solutions to detect financial crime at a significant financial institution. Leading model development with business stakeholders and engineers while maintaining compliance standards.
Working Student at Fraunhofer Institute focusing on Data Science and Natural Language Processing. Involved in AI - driven projects with a flexible work schedule.
Werkstudent*in in Data Science und Natural Language Processing bei Fraunhofer, tätig in KI - gestütztem Wissensmanagement und innovativer KI - Lösungsentwicklung.
Data Science Internship at Engineering focused on empowering digital transformation. Join a team that values innovative solutions and professional growth in IT.
Business Analyst acting as a critical link between business and technical teams at Vodafone. Involves gathering requirements and ensuring technical specifications in telecom projects.
Data Scientist developing statistical models and rules for Allegro's eCommerce platform. Driving insights and collaborating across teams to improve product catalog and selection.
Data Scientist developing statistical models and improving product quality for Allegro's eCommerce platform. Collaborating with cross - functional teams to deliver insights and drive business solutions.
Data Scientist at Imprint leveraging data analytics to enhance co - branded credit card offerings and optimize financial product decisions. Collaborating with cross - functional teams in a high - impact role.