Chubb
Senior Data Scientist
Chubb, Jersey City, New Jersey, United States, 07390
Senior Data Scientist
The North America PRS (Personal Risk Services) Data Science team at Chubb is seeking a data scientist with 4+ years of industry experience to join our fast-paced, high-energy team. This team is responsible for building data pipelines and delivering predictive modeling and data science solutions to our business partners that will meet business objectives and improve key performance metrics.
Job Summary
As a data scientist for PRS, you will develop predictive modeling / machine learning solutions to complex business problems and create value for the business. This position offers exposure to a wide variety of analytic tools and technologies as well as unique challenges in problem-solving. Be ready to leverage internal/external data sources as you develop, deploy, and monitor best-in-class model solutions.
Primary Responsibilities
Mentor Junior Data Scientists and Engineers.
Execute all aspects of analytics initiatives including exploratory data analysis, data preprocessing, model development, model deployment and monitoring.
Thoughtfully identify and construct predictive variables from both internal and external data sources.
Synthesize data to uncover inherent trends, assess the impact of data on business usage, and make recommendations for improvement.
Research, recommend, and implement statistical and other mathematical methodologies appropriate for the given business problem.
Actively contribute to the implementation/deployment of models.
Provide supporting documentation for the models developed including documentation of methodologies used, data issues encountered, and responses to regulatory requests.
Collaborate with business partners and peers within the organization to understand and scope the problem, gather business requirements, and develop robust model solutions that drive improvement in key business metrics.
Effectively communicate with key stakeholders (both technical and non-technical) in written, oral and presentation formats.
Create/Maintain excellent working relationships with business partners across the Chubb organization including Product, Actuarial, IT, and analytics peer groups.
Skills/Experience
Required:
Hands-on experience utilizing both supervised and unsupervised ML (Machine Learning) algorithms.
Excellent understanding of data mining, predictive modeling, and data visualization.
Advanced knowledge of model tuning, evaluation, and operationalization.
Significant programming experience in either Python or R.
Significant programming experience in SQL.
Working knowledge with Git version control.
Ability to communicate effectively to both technical and non-technical audiences in written, oral and presentation formats.
The ability to multi-task, learn new things quickly, and demonstrate excellent problem-solving skills.
Preferred:
Experience in architecting and consuming APIs at scale.
Comfortable with command line (Linux, Windows) scripting.
Experience with at least one other programming language (Python, R, Julia, Scala, Go, Java, C++).
Prior exposure to NoSQL databases.
Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure/AWS/GCP).
Prior exposure to auto-ML platforms or technologies like DataRobot or H2O’s AutoML/Driverless AI.
Experience with Deep Learning libraries (Tensorflow / Keras, PyTorch, MXNet, etc.).
Experience with Text Analytics and Natural Language Processing.
Nice to have:
Experience in personal lines insurance.
Education
If the candidate’s background is Actuarial science, an ideal candidate would have a solid understanding of advanced actuarial techniques and statistical modeling with at least 5 years of experience and 5+ exams completed (ACAS preferred).
If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
Compensation
In Jersey City, NJ the pay range for the role is $101,000 to $172,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found at
Chubb Careers . This range is specific to Jersey City, NJ and may not be applicable to other locations.
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The North America PRS (Personal Risk Services) Data Science team at Chubb is seeking a data scientist with 4+ years of industry experience to join our fast-paced, high-energy team. This team is responsible for building data pipelines and delivering predictive modeling and data science solutions to our business partners that will meet business objectives and improve key performance metrics.
Job Summary
As a data scientist for PRS, you will develop predictive modeling / machine learning solutions to complex business problems and create value for the business. This position offers exposure to a wide variety of analytic tools and technologies as well as unique challenges in problem-solving. Be ready to leverage internal/external data sources as you develop, deploy, and monitor best-in-class model solutions.
Primary Responsibilities
Mentor Junior Data Scientists and Engineers.
Execute all aspects of analytics initiatives including exploratory data analysis, data preprocessing, model development, model deployment and monitoring.
Thoughtfully identify and construct predictive variables from both internal and external data sources.
Synthesize data to uncover inherent trends, assess the impact of data on business usage, and make recommendations for improvement.
Research, recommend, and implement statistical and other mathematical methodologies appropriate for the given business problem.
Actively contribute to the implementation/deployment of models.
Provide supporting documentation for the models developed including documentation of methodologies used, data issues encountered, and responses to regulatory requests.
Collaborate with business partners and peers within the organization to understand and scope the problem, gather business requirements, and develop robust model solutions that drive improvement in key business metrics.
Effectively communicate with key stakeholders (both technical and non-technical) in written, oral and presentation formats.
Create/Maintain excellent working relationships with business partners across the Chubb organization including Product, Actuarial, IT, and analytics peer groups.
Skills/Experience
Required:
Hands-on experience utilizing both supervised and unsupervised ML (Machine Learning) algorithms.
Excellent understanding of data mining, predictive modeling, and data visualization.
Advanced knowledge of model tuning, evaluation, and operationalization.
Significant programming experience in either Python or R.
Significant programming experience in SQL.
Working knowledge with Git version control.
Ability to communicate effectively to both technical and non-technical audiences in written, oral and presentation formats.
The ability to multi-task, learn new things quickly, and demonstrate excellent problem-solving skills.
Preferred:
Experience in architecting and consuming APIs at scale.
Comfortable with command line (Linux, Windows) scripting.
Experience with at least one other programming language (Python, R, Julia, Scala, Go, Java, C++).
Prior exposure to NoSQL databases.
Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure/AWS/GCP).
Prior exposure to auto-ML platforms or technologies like DataRobot or H2O’s AutoML/Driverless AI.
Experience with Deep Learning libraries (Tensorflow / Keras, PyTorch, MXNet, etc.).
Experience with Text Analytics and Natural Language Processing.
Nice to have:
Experience in personal lines insurance.
Education
If the candidate’s background is Actuarial science, an ideal candidate would have a solid understanding of advanced actuarial techniques and statistical modeling with at least 5 years of experience and 5+ exams completed (ACAS preferred).
If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
Compensation
In Jersey City, NJ the pay range for the role is $101,000 to $172,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found at
Chubb Careers . This range is specific to Jersey City, NJ and may not be applicable to other locations.
#J-18808-Ljbffr