Data Scientist II - Gen AI/Python/AWS/SQL

Unum•Portland, ME

2d•$73,300 - $150,500•Hybrid

About The Position

Passionate about AI and data-driven innovation? Join our innovation hub as a Data Scientist II, where you'll help solve high-impact business challenges using machine learning, generative AI, and advanced analytics. In this role, you'll develop proof-of-concept solutions, build and deploy AI models, and collaborate with stakeholders across the enterprise to turn complex data into actionable insights. You'll work in a fast-paced, agile environment that encourages experimentation, continuous learning, and the application of emerging technologies to create measurable business value.

Requirements

Bachelor’s degree in quantitative field is required
4 years of professional experience or equivalent relevant work experience preferred
Deep expertise in at least two of the following skillsets preferred; and competency in the other: Programming & Process automation: Experience with file I/O, database integrations, and APIs to build automated analytics pipelines. Understanding of process research and design, which may be demonstrated through use of DevOps, automation, data mining, web scraping, or object-oriented software is preferred.
Data Visualization: Expertise on at least one visualization tool with working knowledge of others and expertise in static data visualization. Understanding of dynamic data visualization.
Statistics & Statistical modeling: Expertise using statistical inference and regression. Solid understanding of machine learning algorithms. Solid understanding of feature selection and extraction. Conducts end-to-end machine learning tasks from problem synthesis to model deployment.
Data Extraction, Transformation, and Loading: Preferred skills include: Expertise in writing complex SQL queries that join multiple tables/databases. Independently explore databases/tables to identify best data sources to solve business problems.
Demonstrates ability to troubleshoot complex SQL queries with little guidance.
Demonstrates ability to create logical data models by combining data from multiple sources including internal and external data.
Demonstrated communication skills
experience in financial services
leadership experience working with senior management and executive leadership
attention to detail while effectively and independently prioritizing work and managing multiple projects simultaneously.
Demonstrated ability to coach or mentor team members
ability to commit quickly and positively to change.
Viewed as a promoter of change management and leads proof of concept work and prototyping when necessary.

Nice To Haves

Master’s is preferred
4 years of professional experience or equivalent relevant work experience preferred
Deep expertise in at least two of the following skillsets preferred; and competency in the other: Programming & Process automation: Experience with file I/O, database integrations, and APIs to build automated analytics pipelines. Understanding of process research and design, which may be demonstrated through use of DevOps, automation, data mining, web scraping, or object-oriented software is preferred.
Data Visualization: Expertise on at least one visualization tool with working knowledge of others and expertise in static data visualization. Understanding of dynamic data visualization.
Statistics & Statistical modeling: Expertise using statistical inference and regression. Solid understanding of machine learning algorithms. Solid understanding of feature selection and extraction. Conducts end-to-end machine learning tasks from problem synthesis to model deployment.
Data Extraction, Transformation, and Loading: Preferred skills include: Expertise in writing complex SQL queries that join multiple tables/databases. Independently explore databases/tables to identify best data sources to solve business problems.
Demonstrates ability to troubleshoot complex SQL queries with little guidance.
Demonstrates ability to create logical data models by combining data from multiple sources including internal and external data.

Responsibilities

Develop and evaluate machine learning and generative AI solutions
Build proof-of-concept applications to address business needs
Partner with cross-functional teams to identify opportunities and deliver insights
Apply advanced analytics to support strategic decision-making
Contribute to a culture of innovation and continuous improvement
Design and execute analytical solutions using optimization, simulation, data mining and other statistical methods with a focus on delivering actionable business value.
Integrate large volume of data from different sources (including DB2, SQL Server, Web API and Teradata) to create data assets for ad-hoc analyses and larger studies.
Apply validation, aggregation, and reconciliation techniques to create rich modeling-ready data framework.
Construct and tune predictive models to explain and understand observed events, forecast expected behavior, or identify risk through scoring or clustering.
Efficiently interpret results and communicate findings and potential value to influence manager and leadership decision making.
Support integration of solutions within existing business processes using automation techniques.
Understand theory and application of current and emerging statistical methods and tools.
Provides support, training and/or mentorship to lower-level Data Science peers.
Perform other related duties as assigned

Benefits

Health, Vision, Dental
Short & Long-Term Disability
Generous PTO (including paid time to volunteer!)
Up to 9.5% 401(k) employer contribution
Mental health support
Career advancement opportunities
Student loan repayment options
Tuition reimbursement
Flexible work environments
healthcare benefits (health, vision, dental)
insurance benefits (short & long-term disability)
performance-based incentive plans
paid time off
401(k) retirement plan with an employer match up to 5% and an additional 4.5% contribution whether you contribute to the plan or not.