Manager Finance and Insurance Analytics

Ford Marketing and Enterprise Analytics is looking for professionals experienced in Financial Analytics, who are hands-on and can employ many AI techniques from traditional statistical/ML NLP to DL-based sequence models and transformers in their day-to-day work.

based sequence models and transformers in their day-to-day work.

Education Qualification

Master's degree or PhD in a quantitative field such as Statistics, Econometrics, Computer Science, Industrial Engineering, or related disciplines.

On Job Experience

Strong experience with statistical modeling techniques (e. g. , regression, clustering, ANOVA) and tools such as Python, R, SAS
Experience with cloud data platforms, preferably Google Cloud Platform (GCP).
Proven ability to manage and manipulate large datasets using SQL, Teradata, or similar.
Excellent communication skills with the ability to convey complex data insights to a non-technical audience.
Demonstrated ability to work collaboratively and drive projects to successful completion.

Leadership Skills

Be able to synthesize various aspects of the business problem into a coherent whole and provide robust solutions.
Be able to effectively communicate complex quantitative methods and results as easily understood business insights for all levels of business customers.
Develop and inspire others to foster technical and professional expertise and excellence

Desired Skills

Experience with GCP services like BigQuery and AI Platform.
Robust programming skills in Python, SAS, or similar languages.
Prior experience in an analytics role within the financial services sector.

• Develop, validate, and deploy statistical models and AI/ML solutions to drive insights and strategies.
• Collaborate with business partners and data scientists.
• Build and present compelling data visualizations and reports for diverse stakeholders.
• Innovate and improve business tools, including dashboards, automated reporting, and data mining solutions.
• Ensure data quality and solution integrity throughout the analytical process.
• Translate complex quantitative methods into actionable business insights for all levels of the organization.
• Ensure data quality and solution integrity throughout the analytical process.
• Translate complex quantitative methods into actionable business insights for all levels of the organization.