IT AVP – Data Science

Tokio Marine Group of Companies•Bala, KS

1d•$160,000 - $180,000

About The Position

The AVP of Data Science is a pivotal role within the Data Products domain. This role will be responsible for managing and developing teams, building organizational capability, and setting and communicating direction. It will identify opportunities to deploy extensive knowledge of data science techniques, challenging the status quo, and designing and implementing scalable data science outputs and products. The role will drive collaboration with group companies and departments with IT to support our organizational objectives, select the most appropriate tools and technologies, navigate ethical and data challenges, and effectively communicate and present findings. The AVP of Data Science will provide expert advice to evaluate problems that need data science solutions and are proficient in handling large and complex data sets, including structured, unstructured, and semi-structured data. In addition to technical expertise, the AVP of Data Science will play a crucial role in team dynamics and professional development. They will be responsible for managing the Data Science team, planning projects, and building analytical models by leveraging large volumes of data from various sources The role also involves leading the development of analytics-driven products using machine learning, natural language processing, and mathematical techniques to develop powerful science in collaboration with the Emerging Tech. leader. Furthermore, the AVP of Data Science will ensure the integration of AI, predictive analytics, and automation into core business functions, such as underwriting, pricing, and claims processing, while staying ahead of industry trends, regulatory changes, and technological advancements.

Requirements

Proficient in Python, R, or similar programming languages
Experience with SQL and data manipulation in databases
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Strong problem-solving and analytical skills
Excellent communication and presentation abilities
Ability to work independently and collaboratively in a team environment
Bachelor’s degree in data science, Computer Science, Information Systems, or a related field preferred
10+ years of relevant experience
3+ years of experience in implementing data solutions, preferably within the insurance industry
Proficiency in data integration tools (e.g., Informatica, Snowflake, Databricks) and analytics platforms (e.g., Tableau, Power BI, Cognos)
Strong knowledge of insurance operations, including underwriting, claims, and regulatory compliance
Familiarity with programming languages such as SQL, Python, or R.
Exceptional communication skills and ability to collaborate with technical and non-technical stakeholders
Proven project management experience: PMP or Agile certifications are a plus
Ability to weigh business needs against security concerns and articulate to management
Knowledge of organizational politics and political tactics; ability to effectively navigate formal and informal communication and decision-making channels
Knowledge, insight, and understanding of business concepts and processes that are needed for making sound decisions in the context of the company's business; ability to apply this knowledge appropriately to diverse situations
Working knowledge of Microsoft Office, and strong knowledge in Microsoft Excel preferred
Ability to write business requirements and functional specifications
Strong customer service orientation toward Business Units requiring financial consultation (responsive, consultative, collaborative and accurate)
Strong leadership ability; able to work with a group to set its objectives and agenda, generate allegiance to those objectives, and guide and motivate achievement
Strong project management skills: Plan, organize, monitor, and control projects, ensuring efficient utilization of resources, to achieve project objectives and deadlines
Strong interpersonal relationship building skills: able to work with a variety of people and groups in a constructive and collaborative manner
Strong analytical ability with the capability to determine the root cause of problems and issues and provide solutions
Strategic thinking: Applies organizational acumen to identify and maintain focus on key success factors for the organization
Superior attention to detail
Ability to juggle multiple, competing, frequently changing time-sensitive deadlines and priorities
Ability to work independently and without supervision
Ability to work and lead effectively as part of a team

Nice To Haves

Knowledge of big data technologies (e.g., Spark, Hadoop, Snowflake, Databricks) is a plus
Experience with cloud platforms such as AWS, Azure, or Google Cloud
Knowledge of natural language processing (NLP) or computer vision techniques
Understanding of A/B testing and causal inference methodologies
Experience in dashboarding tools such as Tableau or Power BI
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and Big Data technologies (e.g., Hadoop, Spark, SQL a plus)
Knowledge of predictive analytics and machine learning models specific to insurance use cases
Master’s Degree preferred

Responsibilities

Develop predictive models to enhance risk assessment, fraud detection, and customer segmentation strategies
Analyze claims data to identify patterns, improve processing efficiency, and detect fraudulent activity
Work closely with Actuarial teams to optimize pricing models and assess market competitiveness
Build advanced models for risk prediction and mitigation, leveraging structured and unstructured data
Clean, preprocess, and integrate data from multiple sources, including internal systems and external third-party datasets
Oversee the development of the Medalion data architecture for TMNAS and its Group Companies
Identify trends in customer behavior to improve retention, tailor policy offerings, and enhance the overall customer experience
Partner with Underwriting, Actuarial, and Claims teams to align data science initiatives with business objectives
Oversee the creation insights and reports to present insights to non-technical stakeholders, supporting data-driven decisions
Build high performance teams through effective training, mentoring, delegating, and providing feedback to members the Department
Mentors and trains team members to be highly proficient in their job function but also build an environment of trust and the future leaders of TMNAS