ENGINEERINGUK
Senior Data Scientist I (HYBRID)
ENGINEERINGUK, Alpharetta, Georgia, United States, 30239
Employer: LexisNexis Risk Solutions
Location: Alpharetta, Georgia, United States of America
Salary: Competitive
Closing date: 11 Jan 2025
Senior Data Scientist I
About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry-specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. About the Role:
Develops, analyzes, and models operational, economic, management, accounting, and other organizational data to quantify the competitive performance of business segments, evaluate potential operational changes, and design new approaches and methodologies. You Will Be Responsible For:
Researching and developing statistical/machine learning models to analyze structured and unstructured data. Leading the design and development of data acquisition and machine learning models. Ideating, researching, and designing new analytics and data science methodologies. Storing, archiving, indexing, transferring, and analyzing large datasets. Working with peers to share subject matter expertise. Exploring and mining new data sources to optimize existing models. Consulting with internal stakeholders to assess and troubleshoot challenges. Contributing to the team's success using technical expertise. Helping develop a sound business and technical strategy for the team. Establishing high standards that elevate the team's performance. Consistently communicating team goals and achievements. Encouraging internal stakeholders to share best practices. All other duties as assigned. Qualifications:
Preferred Academic Background and Professional Experience
Minimum undergraduate degree in relevant field and 4+ years of relevant work experience. Or a master's degree in a relevant field and 2+ years of relevant work experience. Or a PhD in a relevant field. Technical/Professional Expertise
Able to build or test new processes with senior guidance. Able to scope out and execute new statistical steps with support from senior contacts. Data Skills
Independently creates typical data steps for analysis. Understands novel data steps for analysis. Coding Skills
Works across coding languages used in Data Science (e.g., Python, SQL, R, Java, C++). Chooses the right coding language to implement solutions. Project Management Skills
Develops project milestones and steps for small-scale projects. Independently executes project steps for complex projects. Domain/Industry Skills
Expertise in basic methods common to the discipline. Develops a basic understanding of adjacent approaches. Behavioral Competencies
Establishes stretch goals. Takes initiative and proactively addresses issues. Treats others with respect. Fosters a team environment that emphasizes accountability. Benefits:
Comprehensive health benefits. 401(k) with match and Employee Share Purchase Plan. Wellness platform with incentives and Employee Assistance Programs. Disability and life insurance benefits. Family benefits, including bonding and family care leaves. Health Savings, Health Care, and Commuter Spending Accounts. Paid leave for Employee Resource Groups and volunteering.
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About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry-specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. About the Role:
Develops, analyzes, and models operational, economic, management, accounting, and other organizational data to quantify the competitive performance of business segments, evaluate potential operational changes, and design new approaches and methodologies. You Will Be Responsible For:
Researching and developing statistical/machine learning models to analyze structured and unstructured data. Leading the design and development of data acquisition and machine learning models. Ideating, researching, and designing new analytics and data science methodologies. Storing, archiving, indexing, transferring, and analyzing large datasets. Working with peers to share subject matter expertise. Exploring and mining new data sources to optimize existing models. Consulting with internal stakeholders to assess and troubleshoot challenges. Contributing to the team's success using technical expertise. Helping develop a sound business and technical strategy for the team. Establishing high standards that elevate the team's performance. Consistently communicating team goals and achievements. Encouraging internal stakeholders to share best practices. All other duties as assigned. Qualifications:
Preferred Academic Background and Professional Experience
Minimum undergraduate degree in relevant field and 4+ years of relevant work experience. Or a master's degree in a relevant field and 2+ years of relevant work experience. Or a PhD in a relevant field. Technical/Professional Expertise
Able to build or test new processes with senior guidance. Able to scope out and execute new statistical steps with support from senior contacts. Data Skills
Independently creates typical data steps for analysis. Understands novel data steps for analysis. Coding Skills
Works across coding languages used in Data Science (e.g., Python, SQL, R, Java, C++). Chooses the right coding language to implement solutions. Project Management Skills
Develops project milestones and steps for small-scale projects. Independently executes project steps for complex projects. Domain/Industry Skills
Expertise in basic methods common to the discipline. Develops a basic understanding of adjacent approaches. Behavioral Competencies
Establishes stretch goals. Takes initiative and proactively addresses issues. Treats others with respect. Fosters a team environment that emphasizes accountability. Benefits:
Comprehensive health benefits. 401(k) with match and Employee Share Purchase Plan. Wellness platform with incentives and Employee Assistance Programs. Disability and life insurance benefits. Family benefits, including bonding and family care leaves. Health Savings, Health Care, and Commuter Spending Accounts. Paid leave for Employee Resource Groups and volunteering.
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