Senior Data Scientist

JOB PURPOSE:
This role at client is as unique as it is rewarding because of the IPAAL
Values (Integrity, Passion,
Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion).
The Sr. Data Scientist is responsible for modeling complex business problems and
discovering business insights through the use of statistical, algorithmic, mining, and
visualization techniques. The data scientist contributes to
AF portfolio of products and services, ensuring that business challenges
are met with fit for purpose.
AI-powered solutions.
The Sr. Data Scientist defines and implements machine learning solutions, leading the
development and implementation in accordance with the overall strategy of AF This role will partner with Data.
Architecture, AI, Innovation, IT, and Advanced Analytics to define a framework that
supports current advanced analytics requirements and future AI-enabled innovations.
DEPARTMENTAL EXPECTATION OF EMPLOYEE
Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model
Acts as a role model within and outside AF.
Perform duties as workload necessitates.
Maintains a positive and respectful attitude.
Communicate regularly with the departmental leader about department issues.
Demonstrates flexible and efficient time management and ability to prioritize workload.
Consistently reports to work on time, prepared to perform duties of the position.
Meets Department productivity standards.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Data Science and Exploration:
Translates business needs into advanced analytics requirements to support the
organization and its members.
Proactively mines data warehouses to identify trends and patterns and generates insights
to enhance the experience of our members.
Performs large-scale experimentation to identify hidden relationships between variables in
large datasets.
Research and implement cutting-edge techniques and tools in machine learning/deep
learning/artificial intelligence to make data analysis more efficient.
Determines requirements that will be used to train and evolve deep learning models and
algorithms.
Develops frameworks and processes to analyze unstructured information to enrich the
decision-making capabilities of our members.
Maintains up-to-date knowledge of machine learning and data analytics tools and
techniques.
Strong knowledge of predictive modeling methodology, acting as a catalyst and mentor in
the organization.
Machine Learning Operations:
Ensures that AI models are maintained throughout the lifecycle, ensuring proper monitoring
and observability across environments.
Partners with stakeholders to properly implement ModelOps, ensuring consistency and
integrity in solutions.
Establish and implement explainability frameworks, like Model Context Protocols and
SHAP.
Monitor and optimize models for accuracy, performance, and cost efficiency.
Data Governance and Security
Works with data governance led to establish and enforce data governance standards,
guidelines, processes, and best practices to ensure data quality and integrity.
Implement data protocols to ensure compliance with regulatory requirements and company
policies.
Collaboration and Strategy:
Provides technical leadership and mentorship to junior data team members.
Stays updated on data science techniques and best practices, making recommendations
for continuous improvement.
Experienced at leveraging both structured and unstructured data sources.
ADDITIONAL DUTIES AND RESPONSIBILITIES
Support data observability efforts to ensure the data continuum and enforce governance
standards.
Other duties assigned by manager or project needs.
QUALIFICATIONS
Bachelor's or Master's degree in Computer Science, Information Systems, Data Science,
or a related field.
Minimum of 8 years of experience in data science, machine learning, data management,
data governance, or a related role.
Experience using statistics and machine learning to solve complex business problems.
Experience conducting statistical analysis with advanced statistical software, scripting
languages, and packages.
Experience building and deploying predictive models, web scraping, and scalable data
pipelines.
Technical Skills:
Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud).
Experience with AI tools, such as MS Azure ML, Snowflake CortexAI, Dataiku.
Strong knowledge of data governance, data security, and compliance practices.
Proficiency in programming languages such as Python, R, or SQL.
Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI).
Soft Skills:
Excellent analytical and problem-solving abilities.
Strong communication and interpersonal skills to collaborate with cross-functional teams.
Ability to lead projects and mentor junior staff.
Auto Insurance claims industry experience preferred