Senior Data Scientist - ML Model Development

Carbon Data Solutions; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Carbon Data Solutions is seeking an experienced Senior Data Scientist to design and deploy advanced machine learning models for analytical use cases in banking and finance. You will tackle credit risk modeling, PD, EAD, LGD, and underwriting challenges while delivering scalable solutions.

The role emphasizes strong programming in Python, collaboration with stakeholders, and clear documentation of experiments and results.

Qualifications

• 7-8+ years of analytics experience, preferably in Banking/Financial Services.
• 4-5 years hands-on experience building ML models for analytical use cases.
• Experience with credit risk models like PD, EAD, LGD, underwriting and collections.
• Strong problem-solving and analytical skills with clear communication.

Responsibilities

• Design, implement, and optimize sophisticated machine learning models. Your work will enable us to uncover meaningful patterns, trends, and insights from data, ultimately solving analytical use cases.
• Utilize sophisticated algorithms and methodologies to refine and improve model performance for accurate predictions and outputs.
• Stay updated on latest ML advancements and integrate cutting-edge techniques to improve models.
• Provide data-driven insights and recommendations supporting decision-making and overcoming analytical hurdles.
• Document methodologies, experiments, and results clearly and concisely for both technical and non-technical stakeholders.
• Communicate complex concepts to diverse stakeholders and remain informed about ML developments.

Skills

Python

ML libraries

Credit risk models

Communication

Job description

Job Description Model Development Senior Data Scientist

We are seeking an experienced and highly skilled senior data scientist to join our team, with a focus on machine learning applications and expertise. As a key contributor, you will play a pivotal role in designing and implementing advanced models to tackle analytical challenges and drive business growth for our clients.

Responsibilities:

• Design, implement, and optimize sophisticated machine learning models. Your work will enable us to uncover meaningful patterns, trends, and insights from data, ultimately solving analytical use cases.
• Utilize sophisticated algorithms and methodologies to refine and improve the performance of our models, enabling accurate predictions and actionable outputs for analytical use cases.
• Stay updated on the latest machine learning advancements, actively identifying and integrating cutting‑edge techniques to continuously improve our models and address diverse analytical use cases.
• Provide data‑driven insights and recommendations that support decision‑making processes and enable us to overcome analytical hurdles.
• Document your methodologies, experiments, and results in clear and concise terms. Effectively communicate complex concepts and findings to both technical and non‑technical stakeholders.
• Stay informed about the latest advancements in machine learning (ML) and assist in identifying and adopting cutting‑edge techniques. Enable us to continuously enhance our ML models and effectively address diverse analytical use cases.

Qualifications:

• 7-8+ years of experience in analytics preferably in Banking and Financial Services
• A minimum of 4-5 years of hands‑on experience working on Machine Learning models to solve analytical use cases.
• Experience with credit risk models like PD, customer management models, EAD, LGD, loan management, underwriting models, collections.
• Excellent problem‑solving and analytical skills, with the ability to work on complex projects and deliver high‑quality results.
• Proficiency in Python, and experience with ML related libraries.
• Experience with large‑scale data processing and distributed computing frameworks is a plus.
• Strong communication skills, both written and verbal, with the ability to convey complex ideas to diverse stakeholders.

Join our team of dedicated professionals and contribute to the development of cutting‑edge Machine learning models that solve analytical use cases, enabling data‑driven decision making and delivering actionable insights.