Director, Data Science & Innovation

Job Summary

As the Director, Data Science & Innovation, you will lead a team of highly skilled and experienced data science and analytic professionals with interdisciplinary knowledge ranging from computer science, mathematics, econometrics, and statistics. You will also be responsible for identifying, developing and implementing advanced data science and analytics solutions to solve complex business problems that contribute to improved profitability, cost reduction and process optimization across all Insurance platforms including: Digital, Operations, Sales, Strategy, Pricing, Underwriting and Product. Leveraging leading edge technologies and capabilities, the team applies traditional artificial intelligence and generative AI techniques to help RBC Insurance solve complex business problems, understand the changing business environment, discover new growth opportunities, and determine where business improvements can be made.

What will you do?

1. Lead strategy development relating to the provision of statistical methodology, use and implementation
2. Owns and manages the RBCI GenAI and Traditional AI product strategy, roadmap and implementation, including the management of AI product squads
3. Develop and manage a robust suite of predictive modeling tools and a decision support framework to drive insurance performance and profitability
4. Autonomously advise the RBCI leadership team on methods and use cases of applied statistics and data science as it relates to RBCI strategic goals and priorities
5. Assess and quantify financial and business value of data science initiatives, in partnership with the business
6. Responsible for Data Science research + innovation, including the development of new cutting-edge capabilities
7. Proactively identify opportunities to leverage AI, predictive modeling and analytics solutions within Insurance
8. Coach, train and mentor data science professionals
9. Provides guidance, support and oversight to team relating to data science end-to-end process and execution
10. Build out and scale Data Science team core competencies to support Data Science growth within Insurance
11. Own the delivery of model validation and model performance tracking

Here’s what we need from you:

Must-have

1. 5+ years experience developing machine learning and AI models to solve complex business problems
2. 3+ years people management experience
3. Strong problem solving, analytics and critical thinking mindset
4. AI product management experience, including leading cross-functional teams
5. Proficient in relevant statistical tools including R, Python, SAS/STAT and SAS/Enterprise Miner
6. Solid knowledge of various database environments including Cloud technologies, SQL, Data Lake House (i.e. Snowflake)
7. Experience with Generative AI and Large Language Models technology (i.e. GPT 3.5/4.0, BERT, Falcon, LLaMA)
8. Familiar with ML ops orchestration tools (i.e. Openshift)

Nice to Have

1. Insurance industry experience
2. Experience working in an agile environment
3. Strong relationship management
4. Change management

What’s in it for you?

A Total Rewards program that includes flexible benefits, work/life balance and career development programs and investment and retirement savings plans

Competitive pay and high-earning potential

All the tools, training, and team support you need to grow your business and career

Flexible work/life balance options

Sophisticated RBCI software tools to boost your productivity and grow your business

RBC Insurance is an organization that succeeds by bringing out the best in its people. You’ll be part of a supportive, inclusive team that shares common values – including a fundamental respect for each other. At the heart of this is a commitment to diversity. RBC respects and responds to the many competing and evolving priorities in our lives – so you can focus on what you can do best – putting clients first.

Job Skills

Artificial Intelligence (AI), Big Data Management, Data Mining, Data Science, Decision Making, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language), Statistical Analysis

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