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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - GenAI/Python/AWS/SQL - **Company:** UNUM Group - **Location:** Dunwoody, GA, United States - **Experience:** Expert - **Salary:** $89,400.0 - $183,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Visualization, IBM DB2, Database Queries, Software Debugging, DevOps, Python (Programming Language), Logical Data Models, Machine Learning, Microsoft SQL Server, Object-Oriented Software Development, Standard Sql, SQL Databases, Teradata SQL, Scripting, Freeform SQL, Cloud Platform System, Feature Engineering, Generative AI, Pyspark, Core Data, Feature Selection, Feature Extraction, Databricks - **Published:** May 15, 2026 - **Apply:** https://www.juju.com/job/00000000fzlea4 ## About the Role Bachelor's in a quantitative field required (Master's/PhD preferred) 6+ years of experience in data science or machine learning Strong Python and SQL skills Experience with cloud platforms (AWS preferred; Azure/GCP comparable) Databricks + PySpark experience is a strong plus Background in statistical modeling, ML algorithms, and feature engineering Ability to build automated analytics workflows and work with APIs Strong communication skills with experience influencing senior stakeholders Entrepreneurial mindset, curiosity, and comfort working in fast-moving environments Job Specifications / Qualifications Education + Bachelor's degree in a quantitative field required. + Master's or PhD in a quantitative discipline preferred. Experience + 6+ years of professional experience or equivalent relevant work. + Proven track record leading end-to-end data science projects with measurable business impact. Technical Expertise Core Data Science Capabilities (expert in at least two, strong in others): + **Programming & Automation:** + Python required; experience with automation, DevOps practices, APIs, file I/O, and database integrations. + Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable). + Exposure to object-oriented development and scalable architecture. + **Data Visualization:** + Expertise across multiple visualization tools and techniques. + Ability to tailor visuals to business use cases and audiences. + **Statistics & Machine Learning:** + Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms. + Experience leading large-scale modeling projects end-to-end. + Familiarity with generative AI approaches is a plus. + **Data Engineering / ETL:** + Strong SQL skills; ability to design, debug, and optimize complex queries. + Ability to navigate and explore large databases independently. + Experience combining internal and external data sources. Soft Skills & Business Leadership + Strong communication skills, including the ability to influence senior leaders. + Project management expertise and strong business acumen (financial services experience a plus). + Ability to manage multiple concurrent initiatives in a fast-moving environment. + Comfortable leading engagements and representing analytics with executive leadership. ## Description Analytical Solution Development + Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling. + Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering. + Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs. + Evaluate alternative approaches and select appropriate modeling techniques for each use case. Data Engineering & Preparation + Integrate and transform large volumes of data from diverse sources (e.g., DB2, SQL Server, Teradata, APIs) to support analytics and experimentation. + Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques. + Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance. + Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed. Automation & Deployment + Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms. + Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes. + Play a lead role in operationalizing AI/ML solutions within production environments. Visualization, Insights & Communication + Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences. + Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners. + Translate complex technical work into business-friendly recommendations. Leadership, Mentorship & Collaboration + Coach, mentor, and develop junior data scientists; provide technical guidance and feedback. + Provide leadership on data science initiatives, ensuring outputs meet quality standards. + Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners. + Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members. Innovation & Research + Stay current on emerging statistical methods, machine learning advancements, and generative AI tools. + Conduct independent R&D to prototype new approaches and explore innovative solutions for high-visibility business problems. + Demonstrate entrepreneurial, self-starter mindset with a strong curiosity and continuous-learning orientation. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization](https://www.wearedevelopers.com/videos/253-data-fabric-in-action-how-to-enhance-a-stock-trading-app-with-ml-and-data-virtualization) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)