Python Machine Learning Model Developer

• *Position Title : Python Machine Learning Model Developer
• *Location : New York, NY (Onsite/Hybrid)
• *Experience : 6+ Years
• *Employee Type : Full Time with Benefits
• *Job Description**

We are seeking a highly motivated Machine Learning professional skilled in Python/R to design, develop, and implement financial and risk models. The role involves working with cross‑functional stakeholders, applying statistical and ML techniques on large datasets, and supporting regulatory stress testing and business forecasting activities.

• *Must have skills:
• Develop financial and risk models using
• *Python/R

for regulatory stress testing and enterprise risk management.

• Build model execution workflows for forecasting
• *Balance Sheet, Fee Revenues, Macroeconomic Indicators, Expenses**

, and related risk metrics.

• Apply
• *machine learning, statistical modeling, and data mining**

techniques to enhance model accuracy and performance.

• Conduct sensitivity analysis, scenario analysis, and stress testing impact attribution.
• Collaborate with stakeholders to define project plans, deliverables, and development timelines.
• Coordinate with business, analytics, and technology teams to ensure successful model integration.
• Support coding, testing, deployment, and documentation of financial and ML models.
• Develop tools and automated processes to monitor model performance and stability.
• Conduct statistical validation tests such as
• *regression diagnostics, time‑series checks, hypothesis testing**

, and performance back-testing.

• Document methodologies, assumptions, and validation findings for audit and regulatory purposes.
• Create insights and analytical presentations using
• *Python, JupyterHub**

, and visualization techniques.

• Prepare decks and reports for senior management and risk committees.
• Communicate model logic, results, and performance metrics in clear and concise formats.
• *Required Skills:**
• Strong proficiency in Python (R experience is a plus).
• Knowledge of machine learning algorithms and statistical modeling.
• Experience with regression models, time-series analysis, statistical tests, and ML model evaluation techniques.
• Ability to work with large structured/unstructured financial datasets.
• Excellent written and verbal communication skills.
• Ability to collaborate across teams and manage multiple workstreams.
• Relevant hands-on experience in model development, financial analytics, or risk modeling.
• Strong problem-solving and analytical thinking abilities.

If your Interested, Kindly, share us your resume on

• abuzar.umar@capgemini.com*
• *Life At Capgemini**

Capgemini supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer:

• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits like subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief
• *Disclaimer**

Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship.

Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

• *Salary Transparency**

Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for the tagged location is $80,320 to $96,458 /yearly. This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.