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Certified Medical Assistant (CMA)

New York, NY · On-site

$21/hr

Certified Medical Assistant (CMA) - $21/hour | Full-Time Contract | NHA Cert Required Location: All ... Data Scientists, Help Desk/Desktop Support, Systems Administrators/Engineers, Network ...

DecisionPoint | Cortek

Data Architect

$65.25 - $84/hr

... CMA) operations across all Service components. The Data Architect will define and maintain logical ... Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related ...

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How much do cma data scientist jobs pay per year?

As of Jun 8, 2026, the average yearly pay for cma data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

Data Scientist

Purple Drive Technologies

Jersey City, NJ • On-site

Full-time

Posted 16 days ago

Job description

Overview:
Summary
Key Responsibilities
• Formulate complex optimization problems (nonlinear, nonconvex, stochastic, constrained, multi-objective).
• Build advanced optimization pipelines using:
oSciPy Optimize, PySwarms, mystic, pymoo, Bayesian Optimization.
• Develop custom, complex solvers and hybrid algorithms leveraging open-source optimization frameworks.
• Implement objective functions, constraint models, surrogate models, and penalty formulations.
• Integrate optimization techniques into ML workflows (hyperparameter tuning, black-box optimization, surrogate modeling).
• Conduct convergence, sensitivity, robustness, and stability analysis of optimization methods.
• Scale optimization systems using Python, distributed computing, and numerical acceleration.
• Communicate complex mathematical concepts to cross-functional audiences.
Required Qualifications
• Masters/PhD in Operations Research, Applied Mathematics, Computer Science, Engineering, or related quantitative field.
• Expertise in nonlinear, global, evolutionary, and multi-objective optimization (e.g., NSGA-II/III, CMA-ES, DE).
• Strong knowledge of Bayesian Optimization and Gaussian Process modeling.
• Deep mathematical foundation (numerical methods, probability, linear algebra).
• Proficiency in the Python scientific ecosystem (NumPy, SciPy, pandas, scikit-learn).
• Demonstrated ability to design custom solvers for high-dimensional, ambiguous, or poorly behaved optimization landscapes.

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