Senior Data Scientist

Arbitration Forums Inc.•Tampa, FL

10h•Remote

About The Position

This role at Arbitration Forums is as unique as it is rewarding because of the AF 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 Arbitration Forums 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 Arbitration Forums, Inc. 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.

Requirements

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.
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).
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.

Nice To Haves

Auto Insurance claims industry experience preferred.

Responsibilities

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.
Researches and implements 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.
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.
Works with the data governance lead to establish and enforce data governance standards, guidelines, processes, and best practices to ensure data quality and integrity.
Implements data protocols to ensure compliance with regulatory requirements and company policies.
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.
Support data observability efforts to ensure the data continuum and enforce governance standards.
Other duties as assigned by manager or project needs.