What are the responsibilities and job description for the Data Scientist-Statistics OR Operations Research position at Jobs via Dice?
Established nearly two centuries ago, FM is a leading mutual insurance company whose capital, scientific research capability and engineering expertise are solely dedicated to property risk management and the resilience of its policyholder-owners. These owners, who share the belief that the majority of property loss is preventable, represent many of the world's largest organizations, including one of every four Fortune 500 companies. They work with FM to better understand the hazards that can impact their business continuity to make cost-effective risk management decisions, combining property loss prevention with insurance protection.
As a Data Scientist, you will focus on translating business needs into analytics, interpretation of analytics into business applications, sophisticated technologies, and artificial intelligence solutions. This role will allow you to innovate, explore, and build solutions for FM using new technologies. You will develop and apply statistics, artificial intelligence, machine learning, and deep learning to various business problems in loss prevention.
You'll be part of our innovative and diverse team of sophisticated data and analytics professionals. You'll work alongside multiple departments, including operations, innovation, business technology transformation, underwriting, and engineering. Through constant learning, innovation, discovery, and collaboration you'll not only help FM deliver on the promise of loss prevention, but you'll also grow your career and the scope of your impact across our company.
Using your creativity and applying a vast array of techniques and tools, you will plan, conduct, and advise the development and evaluation of real-world, large-scale problems using artificial intelligence/machine learning with minimal or limited supervision.
Your projects will be interesting, exciting and ambitious! You will use statistics to advance the mission and goals of FM.
Ph.D. in Statistics, Biostatistics or Operational Research with 2 years of industry experience or a Master's degree with 5 years of industry working experience in data science modelling
5 years of experience of data processing, statistical analysis and modelling using tools such as Python,R, or SQL
2 years of experience of working with cloud data analytics platform, such as Databricks
Advanced Knowledge and Working Experience in:
Generalized Linear Models (Logistic Regression, Zero-Inflated Model, etc.)
Model Regularization
Probability Distributions
Hypothesis testing
Statistical Inference
Machine Learning (Random Forest, Clustering, Gradient Descent, Gradient Boosting, etc.)
Simulation
Experiment Design
Non-Parametric Statistics
Experience as the lead role of full-cycle data science projects
Working experience in risk management and/or property insurance is strongly preferred
Compensation, Grade, and Job Title will be determined based on qualifications, experience, and technical skillset.
The position is eligible to participate in FM's comprehensive Total Rewards program that includes an incentive plan, generous health and well-being programs, a 401(k) and pension plan, career development opportunities, tuition reimbursement, flexible work, paid time off allowances and much more.
FM is an Equal Opportunity Employer and is committed to attracting, developing, and retaining a diverse workforce.
As a Data Scientist, you will focus on translating business needs into analytics, interpretation of analytics into business applications, sophisticated technologies, and artificial intelligence solutions. This role will allow you to innovate, explore, and build solutions for FM using new technologies. You will develop and apply statistics, artificial intelligence, machine learning, and deep learning to various business problems in loss prevention.
You'll be part of our innovative and diverse team of sophisticated data and analytics professionals. You'll work alongside multiple departments, including operations, innovation, business technology transformation, underwriting, and engineering. Through constant learning, innovation, discovery, and collaboration you'll not only help FM deliver on the promise of loss prevention, but you'll also grow your career and the scope of your impact across our company.
Using your creativity and applying a vast array of techniques and tools, you will plan, conduct, and advise the development and evaluation of real-world, large-scale problems using artificial intelligence/machine learning with minimal or limited supervision.
Your projects will be interesting, exciting and ambitious! You will use statistics to advance the mission and goals of FM.
Ph.D. in Statistics, Biostatistics or Operational Research with 2 years of industry experience or a Master's degree with 5 years of industry working experience in data science modelling
5 years of experience of data processing, statistical analysis and modelling using tools such as Python,R, or SQL
2 years of experience of working with cloud data analytics platform, such as Databricks
Advanced Knowledge and Working Experience in:
Generalized Linear Models (Logistic Regression, Zero-Inflated Model, etc.)
Model Regularization
Probability Distributions
Hypothesis testing
Statistical Inference
Machine Learning (Random Forest, Clustering, Gradient Descent, Gradient Boosting, etc.)
Simulation
Experiment Design
Non-Parametric Statistics
Experience as the lead role of full-cycle data science projects
Working experience in risk management and/or property insurance is strongly preferred
Compensation, Grade, and Job Title will be determined based on qualifications, experience, and technical skillset.
The position is eligible to participate in FM's comprehensive Total Rewards program that includes an incentive plan, generous health and well-being programs, a 401(k) and pension plan, career development opportunities, tuition reimbursement, flexible work, paid time off allowances and much more.
FM is an Equal Opportunity Employer and is committed to attracting, developing, and retaining a diverse workforce.