Co-op Student

at  Resolution Life

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Co-op with Resolution Life US
Position Summary:
Resolution Life is looking to expand our team of experts that work together to convert vast amounts of business and consumer data into actionable insights, improved business decisions, and positive customer interactions. The group’s analytics are used to build, retain and strengthen our relationship with individual policyholders, advisors and beneficiaries, and to improve our business processes across the enterprise.
Position Description:
Resolution Life is looking for a Co-op AI Data Scientist who will help our teams to leverage data to drive insights and effect change in the organization.
This role will initially align with the Enterprise AI/BI squad to leverage our data lake house architecture and expand our functional capabilities such as automated recalculation of assets, liabilities, and metrics in domains such as experience studies, capital reporting and valuation. It can also encompass expansion to more technical capability development such as MLOps, De-identification, and Deep Learning.

Knowledge & Experience:

• Progression towards degree, preferably in data science/engineering, computer science, engineering, math/physics, actuarial science or a related field of study;
• Strong communication skills, particularly in explaining potentially complicated subjects in a relatable fashion
• Deep understanding of Probability & Statistics as applies to ML: Conditional probability, Bayes Rule, Distributions and analysis methods for validating models
• Passion for innovation and “can do” attitude to thrive in a fast-paced environmen

At Resolution Life, we have identified the following critical skills which are key to success in our culture:

• Customer Focused: Passionate drive to delight our customers and offer unique solutions that deliver on their expectations.
• Critical Thinking: Thoughtful process of analyzing data and problem solving data to reach a well-reasoned solution.
• Team Mentality: Partnering effectively to drive our culture and execute on our common goals.
• Business Acumen: Appreciation and understanding of the financial services industry in order to make sound business decisions.
• Learning Agility: Openness to new ways of thinking and acquiring new skills to retain a competitive advantage

• Partner with Business Analysts and Architects to develop technical architectures for strategic enterprise projects and initiatives.
• Performing data analysis to deliver actionable business insights
• Generating clear and meaningful profiles and segmentations of Resolution’s customers and businesses
• Enable big data and batch/real-time analytical solutions that leverage emerging technologies
• Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
• Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering in order to improve our productivity as a team
• Working with the predictive modeling team to ensure that models are accurate and reflect business reality
• Evaluating processes and initiatives to measure impact and make appropriate recommendations based on results
• Coaching others in machine learning and cloud best practices

Knowledge & Experience:

• Progression towards degree, preferably in data science/engineering, computer science, engineering, math/physics, actuarial science or a related field of study;
• Strong communication skills, particularly in explaining potentially complicated subjects in a relatable fashion
• Deep understanding of Probability & Statistics as applies to ML: Conditional probability, Bayes Rule, Distributions and analysis methods for validating models
• Passion for innovation and “can do” attitude to thrive in a fast-paced environment

Preferred but not required:

• AWS Certification, preferably in ML Specialty or Data Analytics
• Working knowledge of in utilizing AWS services (Redshift, Athena, EMR, Glue, Sagemaker)
• Experience with feature engineering, feature stores, Auto ML, containerization, MLOps
• Software Engineering experience: library calls, REST APIs, database queries, Python coding
• Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, etc.
• Conduct advanced statistical analysis to provide actionable insights, identify trends, reduce bias and measure performance
• Able to present complex findings in a business-friendly manner, including appropriate and effective data visualizations using tools such as Quicksight
• A proven track record of using analytics to deliver insight and quantify benefits
• One or more specialized skillsets that could be leveraged within analytics (ex. Predictive Modeling, Machine Learning, Deep Learning, 3rd Party & 1st Party data integration, Natural Language Processing (NLP), Computer Vision and Digital Image Processing)
• Understanding of business concepts relevant to one or more of Resolution’s core capabilities (Life, Annuity, Insurance, Asset Management) plus but not essential
• Experience with agile ways of working is a plus but not essential
• Preference (not required) to have experience in applying data science within Life/Annuity domain(s) including: Capital, Risk, Investments, Finance, Valuation, or Experience Studies
• Preference (not required) Fellow of the Society of Actuaries (FSA) designation or progression towards

Critical Skills

At Resolution Life, we have identified the following critical skills which are key to success in our culture:

• Customer Focused: Passionate drive to delight our customers and offer unique solutions that deliver on their expectations.
• Critical Thinking: Thoughtful process of analyzing data and problem solving data to reach a well-reasoned solution.
• Team Mentality: Partnering effectively to drive our culture and execute on our common goals.
• Business Acumen: Appreciation and understanding of the financial services industry in order to make sound business decisions.
• Learning Agility: Openness to new ways of thinking and acquiring new skills to retain a competitive advantage.