7 дней назад
Quantitative Analytics & Model Analyst Senior (AI/MLOps)
86 250 - 172 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Quantitative Analytics & Model Analyst Senior (AI/MLOps): Building and deploying scalable AI and machine learning solutions, reusable model lifecycle frameworks, and production infrastructure with an accent on model deployment, monitoring, cloud platforms, and operational reliability. Focus on developing containerized AI/ML solutions, managing releases and validation, and solving complex model risk, data quality, and regulatory analysis challenges.
Location: In-office in Tysons Corner, VA; Pittsburgh, PA; or Cleveland, OH
Base salary: $86,250.00–$172,500.00 annually, plus incentive eligibility.
Company
is a financial services company focused on banking, quantitative analysis, risk management, and customer solutions.
What you will do
- Design, engineer, deploy, and support scalable AI, machine learning, GenAI, and agentic AI solutions.
- Build reusable frameworks and components for model development, integration, testing, deployment, and monitoring.
- Operate analytical and machine learning solutions in enterprise production environments alongside data scientists and engineering teams.
- Manage model lifecycle activities, including releases, version control, validation, performance monitoring, and optimization.
- Develop and validate container images in OpenShift and support automation, orchestration, infrastructure-as-code, and CI/CD initiatives.
- Analyze model risk, data quality, model limitations, and regulatory compliance requirements, providing recommendations to stakeholders.
Requirements
- Bachelor’s degree in computer science, information systems, data science, engineering, mathematics, statistics, or a related quantitative field.
- 3+ years of relevant or direct industry experience.
- Experience with machine learning, analytics, software engineering, DevOps, MLOps, and enterprise solution deployment.
- Programming experience in Python, R, or PySpark, with working knowledge of SQL.
- Experience with Git, Jenkins, Docker, JIRA, Confluence, CI/CD, cloud platforms such as AWS or Azure, and release management.
- Strong analytical, problem-solving, communication, presentation, stakeholder engagement, and cross-functional collaboration skills.
Nice to have
- Banking, financial services, lending, credit risk, or risk management experience.
- Familiarity with model governance, model monitoring, production support, data engineering, and enterprise data ecosystems.
Culture & Benefits
- In-office workplace with a focus on collaboration, inclusion, and professional development.
- Medical, dental, vision, life, disability, HSA, 401(k) match, pension, and stock purchase benefits, subject to eligibility.
- Paid holidays, vacation, parental leave, occasional absence days, and other paid time off.
- Educational assistance, wellness programs, dependent care support, and family-related reimbursements.
- Employment visa sponsorship and STEM OPT participation are not available.
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