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    Lead Machine Learning Engineer - Chicago, IL, United States - QBE Insurance

    QBE Insurance
    QBE Insurance Chicago, IL, United States

    2 weeks ago

    QBE Insurance background
    Description

    Primary Details

    Time Type: Full time Worker Type: Employee The Opportunity QBE is on the lookout for a Lead Machine Learning Engineer with deep expertise in developing and deploying advanced machine learning models and solutions. This role is central to driving QBE's innovative insurance solutions forward, including Pricing, Machine Learning, and by leveraging the latest AI technologies. The ideal candidate will have a strong foundation in machine learning engineering, software development, and team leadership. Additionally, the role demands a creative approach to problem-solving, effective mentorship, and the ability to foster strong collaborative relationships across the organization. Primary Responsibilities
    • Develop and implement machine learning models to drive innovations in fraud detection, pricing strategies, and claim processing, ensuring QBE's competitive edge in tech-driven insurance solutions.
    • Collaborate closely with business analysts and data scientists to transform complex business needs into technical specifications, thereby driving actionable insights and enhancing underwriting, pricing, and claims performance.
    • Lead the integration of machine learning models into production, focusing on scalability, reliability, and adherence to engineering best practices.
    • Ensure the scalability and efficiency of machine learning deployments through robust infrastructure management, including developing and maintaining deployment pipelines.
    • Engage in active mentorship and technical leadership within the team, promoting a culture of innovation, continuous learning, and quality.
    • Manage cross-functional projects, coordinating with internal teams and external partners to prioritize activities and deliver on strategic objectives.
    • Maintain compliance with regulatory requirements, ensuring all model implementations and documentation meet industry standards.
    Required Education
    • Bachelor's Degree or equivalent combination of education and work experience
    Required Experience
    • 5 years relevant experience
    Preferred Competencies/Skills
    • Excellent project management, collaboration, and communication skills, capable of leading complex projects and influencing stakeholders at all levels.
    • Excellent all-around software development skill in Python.
    • Experience working in cloud environments such as Azure, AWS, or GCP and knowledge of their AI and ML services.
    • Experience in running a large program or several projects simultaneously.
    • Proficiency in SQL for analysis and data extraction.
    • Advanced knowledge in machine learning engineering practices, including MLOps tools (MLflow, Kubeflow, TFX) to streamline the machine learning lifecycle.
    • Familiarity with containerization and orchestration technologies (Docker, Kubernetes) for scalable ML deployments.
    • Experience with TensorFlow, PyTorch, transformers, LangChain, numpy, pandas, polars, and related.
    • Excellent communication and collaboration skills.
    Preferred Education Specifics
    • Degree qualified (or equivalent) in Computer Science, Engineering, Machine Learning, Mathematics, Statistics, or related discipline
    • 3+ years of experience with design and architecture, data structures, and testing/launching software products.
    • 2+ years in ML engineering with production-level deployments.
    Preferred Licenses/Certifications
    • Certified Specialist in Predictive Analytics (CAS) or other data science related certifications
    Preferred Knowledge
    • Strong understanding of data and model quality monitoring systems, and developing data validation frameworks.
    • Expertise in advanced model optimization techniques, including fine-tuning and the development and deployment of Retrieval-Augmented Generation (RAG) models for enhanced AI performance.
    • Proficient in Git and trunk-based branching strategies.
    • Guide the team in adopting CI/CD practices, code review processes, and automated testing frameworks for ML systems.
    • Strong understanding of software design principles.
    • Skilled in implementing data and model quality monitoring systems and developing data validation frameworks.
    • Proven proficiency in developing and executing Bash scripts for automation and system management tasks.
    • Understand policyholder characteristics and insurance product attributes as needed to improve model performance.
    • Creativity and curiosity for solving complex problems.
    About QBE We can never really predict what's around the corner, but at QBE we're asking the right questions to enable a more resilient future by helping those around us build strength and embrace change to their advantage. We're an international insurer that's building momentum towards realizing our vision of becoming the most consistent and innovative risk partner. And our people will be at the center of our success. We're proud to work together, and encourage each other to enable resilience for our customers, our environment, our economies and our communities. With more than 12,000 people working across 27 countries, we're big enough to make a real impact, but small enough to provide a friendly workplace, where people are down-to-earth, passionate, and kind. We believe this is our moment: What if it was yours too? Your career at QBE — let's make it happen US Only - Travel Frequency
    • Infrequent (approximately 1-4 trips annually)
    US Only - Physical Demands
    • General office jobs: Work is generally performed in an office environment in which there is not substantial exposure to adverse environmental conditions. Must have the ability to remain in a stationary position for extended periods of time. Must be able to operate basic office equipment including telephone, headset and computer. Incumbent must be able to lift basic office equipment up to 20 lbs.
    US Only - Disclaimer
    • To successfully perform this job, the individual must be able to perform each essential job responsibility satisfactorily. Reasonable accommodations may be made to enable an individual with disabilities to perform the essential job responsibilities.
    Job Type
    • Individual Contributor
    Global Disclaimer
    • The duties listed in this job description do not limit the assignment of work. They are not to be construed as a complete list of the duties normally to be performed in the position or those occasionally assigned outside an employee's normal duties. Our Group Code of Ethics and Conduct addresses the responsibilities we all have at QBE to our company, to each other and to our customers, suppliers, communities and governments. It provides clear guidance to help us to make good judgement calls.
    Compensation Base pay offered will vary depending on, but not limited to education, experience, skills, geographic location and business needs. Annual Salary Range: $121,000 - $182,000 AL, AR, AZ, CO (Remote), DE, FL, GA, IA, ID, IL (Remote), IN, KS, KY, LA, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NV, OH, OK, OR, PA, SC, SD, TN, TX (Remote, Plano), UT, VA, VT, WI, WV and WY * * * * * Annual Salary Range: $133,000 - $200,000 CA (Remote, Fresno, Irvine and Woodland), Greenwood Village CO, CT, Chicago IL, MA, MD, NY (Remote), RI, Houston TX and WA * * * * * Annual Salary Range: $152,000 - $228,000 San Francisco CA, NJ and New York City NY Benefit Highlights You are more than your work – and QBE is more than a workplace, which is why QBE provides you with the benefits, support and flexibility to help you concentrate on living your best life personally and professionally. Employees scheduled over 30 hours a week will have access to comprehensive medical, dental, vision and wellbeing benefits that enable you to take care of your health. We also offer a competitive 401(k) contribution and a paid-time off program. In addition, our paid-family and care-giver leaves are available to support our employees and their families. Regular full-time and part-time employees will also be eligible for QBE's annual discretionary bonus plan based on business and individual performance. At QBE, we understand that exceptional employee benefits go beyond mere coverage and compensation. We recognize the importance of flexibility in the work environment to promote a healthy balance, and we are committed to facilitating personal and professional integration for our employees. That's why we offer the opportunity for hybrid work arrangements. If this role necessitates a hybrid working model, candidates must be open to attending the office 8-12 days per month. This approach ensures a collaborative and supportive work environment where team members can come together to innovate and drive success. How to Apply: To submit your application, click "Apply" and follow the step by step process. Equal Employment Opportunity: QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates. Application Close Date: 17/04/2024 11:59 PM How to Apply: To submit your application, click "Apply" and follow the step by step process. Equal Employment Opportunity: QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates. #J-18808-Ljbffr
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