Remote Data Science Manager – Finance AI & Analytics

MaziCTools; Los Angeles (CA); Híbrido; USD 41.000 - 56.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Base pay competitive

Performance bonuses

Retirement matching 6%

Comprehensive benefits

Parental leave

Wellness programs

Descripción de la vacante

American Express is seeking Chiefs and information Science experts to apply statistical methods and AI techniques to improve forecasting and business insights. The role involves collaborating with finance, risk and business teams to drive data-driven decisions.

The position requires a graduate degree in statistics, mathematics, or related fields and at least two years of applied experience in quantitative modeling, with strong Python/R/SAS skills and SQL-based data extraction.

Formación

• Graduate degree in Statistics, Math, Software Engineering, Engineering, Data Systems, or related field.
• 2 years of experience applying statistical and econometric modeling to business problems in finance.
• Experience with quantitative, numerical and statistical concepts and data processing techniques.
• Proficiency with SQL, Teradata, HiveQL for data extraction and manipulation.
• Experience in applying AI methods using Python, R and SAS.

Responsabilidades

• Research and communicate advanced quantitative methods to drive business insights and forecasts.
• Collaborate with finance, risk and business teams to derive strategic insights using visualization and reporting tools.
• Develop and convey models and analyses to support business objectives.

Conocimientos

Python

R

SAS

AI methods

Statistical modeling

Time series analysis

Data visualization

Educación

Graduate degree in Statistics/Math/Software Engineering/Data Systems or related field

Herramientas

SQL

Teradata

HiveQL

Descripción del empleo

American Express is seeking Chiefs and information Science experts to apply statistical methods and AI techniques to improve forecasting and business insights. The role involves collaborating with finance, risk and business teams to drive data-driven decisions.

The position requires a graduate degree in statistics, mathematics, or related fields and at least two years of applied experience in quantitative modeling, with strong Python/R/SAS skills and SQL-based data extraction.