Lead Machine Learning Systems Engineer at Everest Re Group in Warren, NJ
It's an exciting time for Everest Re Group, Ltd. (Everest)! As we continue on our journey, we see significant opportunity ahead of us to expand our reach, build diversity, and enhance our capabilities in critical markets. Everest is a leading global reinsurance and insurance provider, operating for nearly 50 years through subsidiaries in the Bermuda, Canada, Europe, Singapore, US, and other territories. Our strengths include extensive product and distribution capabilities, a strong balance sheet, and an innovative culture. Throughout our history, Everest has maintained its discipline and focuses on creating long-term value through underwriting excellence and strong risk and capital management. But the most critical asset in this organization is our people. At Everest, we are committed to the development of our people. We offer dynamic training & professional development to our employees. You will benefit from career development and learning opportunities that will let you set career goals and fulfill them, including:
o Generous tuition/continuing education reimbursement o Mentoring opportunities o Flexible work arrangements o Talent development initiatives o Networking groups Everest is a growth company with $10.5 Billion of Gross Written Premium offering Property, Casualty and specialty products among others, through its various operating subsidiaries located in key markets around the world. Everest has been a global leader in reinsurance with a broad footprint, deep client relationships, underwriting excellence, responsive service and customized solutions. Our insurance arm draws upon impressive global resources and financial strength to tailor each policy to meet the individual needs of our customers. Our financial strength is evident in Financial Agency Ratings of:
A
A. M. Best, A
S&P Global and A1 Moody's Investor Service. We are a market leader for our broad diversified income streams, strong underlying underwriting performance with reduced volatility and strong cash flow. We take pride in being known in the industry as nimble, entrepreneurial and responsive. Although we are currently in the North American market, we see great opportunity to expand our markets. To support this, we are currently looking for a highly motivated Lead Machine Learning Systems Engineer to provide solutions in the areas of data distribution, predictive analysis and ML Ops. The ideal candidate must have hands on experience across the Predictive Analytics lifecycle; from platform architecture, exploration/prototyping, development, deployment, operations to integration with other systems. The candidate will work with various technical and business team across the organization to develop and operationalize data driven analytical solutions and applications. Responsibilities and areas of engagement include but are not limited to:
Help to influence the design and development of predictive models using advanced machine learning techniques to drive business value Design and implement target analytics environment which allows integration of multiple data sources, models, and modern software tools and performing predictive analytics at scale. Conduct data preparation and cleansing and building data pipelines to support modeling and operational needs. Work closely with engineers to deploy models in production; support model upgrades and integrate production models with existing systems. Deploy tools for continuous monitoring of model performance and enhancing the algorithms. Build strong working relationships and develop deep partnership with the Business, PMO, Infrastructure & Security team and Enterprise Architecture to advance analytics goals. Help to conceptualize Proof of Concept (POC) to prototype new product development and partner with a cross functional team of Business Partners, Product Manager, Software Engineers and Platform Engineers to bring POC to production Become our resident subject matter expert on Machine Learning, ML Ops and Predictive Modeling and a mentor to our junior data resources Keep current on latest computing trends by Identifying, evaluating, and deploying new Machine Learning tools and new data sources (internal and external), and driving adoption Challenge existing thought processes and actively work in cross disciplinary groups and make a case using rich data and presentation. Work Experience and
Qualifications:
Bachelor's degree from an accredited college or university (computer science with statistics/ML a plus) Required R/Python/PySpark programming skills and knowledge of various ML libraries. 5
years of relevant work in Data Engineering and Analytics, with a deep understanding of various data distribution techniques (real-time ingestion/streaming/automation). Demonstrated experience working with the full-stack AI/ML solutions/technologies. Experience in SQL Big Data Cluster, ML Flow, Data Lake a strong plus Advanced knowledge of data analysis, predictive analytics, machine learning and data visualization Strong Analytics and AI/ML background with expertise in one or more of these areas:
(but not limited) - Forecasting, Anomaly detection, Real-Time analytics, Cognitive Experience in the operation and scale of predictive analytics and machine learning models in live production environment is required Conceptual understanding of Model Governance practices a nice to have Strong analytical, problem-solving, and decision-making ability Ability to take direction, demonstrate excellent teamwork, and work well with limited supervision Excellent written and verbal communication skills Highly motivated and self-directed with the ability to see the long-term vision
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine Learning, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
o Generous tuition/continuing education reimbursement o Mentoring opportunities o Flexible work arrangements o Talent development initiatives o Networking groups Everest is a growth company with $10.5 Billion of Gross Written Premium offering Property, Casualty and specialty products among others, through its various operating subsidiaries located in key markets around the world. Everest has been a global leader in reinsurance with a broad footprint, deep client relationships, underwriting excellence, responsive service and customized solutions. Our insurance arm draws upon impressive global resources and financial strength to tailor each policy to meet the individual needs of our customers. Our financial strength is evident in Financial Agency Ratings of:
A
A. M. Best, A
S&P Global and A1 Moody's Investor Service. We are a market leader for our broad diversified income streams, strong underlying underwriting performance with reduced volatility and strong cash flow. We take pride in being known in the industry as nimble, entrepreneurial and responsive. Although we are currently in the North American market, we see great opportunity to expand our markets. To support this, we are currently looking for a highly motivated Lead Machine Learning Systems Engineer to provide solutions in the areas of data distribution, predictive analysis and ML Ops. The ideal candidate must have hands on experience across the Predictive Analytics lifecycle; from platform architecture, exploration/prototyping, development, deployment, operations to integration with other systems. The candidate will work with various technical and business team across the organization to develop and operationalize data driven analytical solutions and applications. Responsibilities and areas of engagement include but are not limited to:
Help to influence the design and development of predictive models using advanced machine learning techniques to drive business value Design and implement target analytics environment which allows integration of multiple data sources, models, and modern software tools and performing predictive analytics at scale. Conduct data preparation and cleansing and building data pipelines to support modeling and operational needs. Work closely with engineers to deploy models in production; support model upgrades and integrate production models with existing systems. Deploy tools for continuous monitoring of model performance and enhancing the algorithms. Build strong working relationships and develop deep partnership with the Business, PMO, Infrastructure & Security team and Enterprise Architecture to advance analytics goals. Help to conceptualize Proof of Concept (POC) to prototype new product development and partner with a cross functional team of Business Partners, Product Manager, Software Engineers and Platform Engineers to bring POC to production Become our resident subject matter expert on Machine Learning, ML Ops and Predictive Modeling and a mentor to our junior data resources Keep current on latest computing trends by Identifying, evaluating, and deploying new Machine Learning tools and new data sources (internal and external), and driving adoption Challenge existing thought processes and actively work in cross disciplinary groups and make a case using rich data and presentation. Work Experience and
Qualifications:
Bachelor's degree from an accredited college or university (computer science with statistics/ML a plus) Required R/Python/PySpark programming skills and knowledge of various ML libraries. 5
years of relevant work in Data Engineering and Analytics, with a deep understanding of various data distribution techniques (real-time ingestion/streaming/automation). Demonstrated experience working with the full-stack AI/ML solutions/technologies. Experience in SQL Big Data Cluster, ML Flow, Data Lake a strong plus Advanced knowledge of data analysis, predictive analytics, machine learning and data visualization Strong Analytics and AI/ML background with expertise in one or more of these areas:
(but not limited) - Forecasting, Anomaly detection, Real-Time analytics, Cognitive Experience in the operation and scale of predictive analytics and machine learning models in live production environment is required Conceptual understanding of Model Governance practices a nice to have Strong analytical, problem-solving, and decision-making ability Ability to take direction, demonstrate excellent teamwork, and work well with limited supervision Excellent written and verbal communication skills Highly motivated and self-directed with the ability to see the long-term vision
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine Learning, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
|
|
 | |
