Senior Analyst Data Science

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them. Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself. Empower India Data Science team is looking for a Sr. Analyst who can apply data science, machine learning, and emerging AI technologies to solve complex business problems and deliver meaningful business outcomes. The ideal candidate will understand the business problem, identify and analyze relevant data, develop analytical and AI-driven solutions, and translate results into meaningful and actionable insights. The candidate should have strong analytical and problem-solving skills with hands-on experience in Python, SQL, Data Science, and Machine Learning, along with an interest in developing and deploying modern Generative AI and cloud-based solutions.

Role Responsibilities: Understand complex business problems and translate them into analytical, Data Science, Machine Learning, or AI use cases. Understand data requirements; collect, clean, transform, analyze, and interpret data from multiple sources. Produce meaningful insights using statistical, analytical, and data modeling techniques and interpret results within the appropriate business context. Develop Machine Learning and statistical models for use cases such as forecasting, classification, regression, segmentation, clustering, anomaly detection, and optimization. Explore and develop Generative AI and Large Language Model (LLM) solutions for applicable business use cases. Develop AI-enabled solutions using Amazon Bedrock or similar foundation-model platforms, including use cases such as summarization, information extraction, classification, question answering, and knowledge-based applications. Support development of Retrieval-Augmented Generation (RAG), prompt engineering, and AI Agent use cases where appropriate. Use Python and SQL to develop reusable data processing, analytical, Machine Learning, and AI solutions. Deploy or integrate analytical, ML, and AI solutions using AWS services such as AWS Lambda, Amazon S3, Amazon Bedrock, or other appropriate cloud technologies. Develop and automate analytical reporting and visualizations using Amazon QuickSight, Power BI, Tableau, or similar tools where required. Perform model validation, testing, evaluation, and monitoring to ensure solutions are accurate, reliable, and appropriate for the intended business use. Handle assigned projects end-to-end and independently manage deliverables, timelines, risks, and stakeholder expectations. Present analytical findings, model results, recommendations, and AI solutions to senior stakeholders in a clear and business-focused manner. Collaborate with business, technology, engineering, analytics, and other cross-functional teams to deliver scalable solutions. Work with management to prioritize business, analytical, AI, and information needs. Continuously evaluate emerging AI, Machine Learning, and Data Science technologies and identify opportunities where they can create business value. Educational Qualification: Graduate / Post-graduate degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Finance, Business Analytics, or another related quantitative discipline. Required Experience: 2–6 years of experience working in Data Science, Advanced Analytics, Machine Learning, Artificial Intelligence, or a related field. Strong hands-on experience using Python and SQL for data analysis, modeling, and solution development. Experience applying statistical and Machine Learning techniques to solve real-world business problems. Experience handling Data Science or analytical projects end-to-end, from understanding the business problem through analysis, modeling, validation, and presentation of results. Experience working with large and complex datasets and performing data preparation, feature engineering, exploratory data analysis, and model evaluation. Exposure to cloud platforms such as AWS for Data Science, Machine Learning, analytics, or AI workloads. Strong attention to detail with an ability and willingness to learn new AI technologies, tools, and analytical techniques. Required Skills and Competencies: Strong knowledge of Python, SQL, Data Science, Machine Learning, and statistical modeling. Strong understanding of techniques such as Regression, Classification, Clustering, Segmentation, Time Series, Forecasting, Feature Engineering, and Model Evaluation. Experience with common Python Data Science and Machine Learning libraries and frameworks. Strong analytical skills with the ability to understand business problems, identify relevant data, perform analysis, and interpret results. Understanding of modern Generative AI and Large Language Model (LLM) concepts. Familiarity with concepts such as prompt engineering, embeddings, vector search, Retrieval-Augmented Generation (RAG), and AI Agents. Exposure to Amazon Bedrock or similar Generative AI / foundation-model platforms is preferred. Experience deploying or integrating analytical, Machine Learning, or AI solutions using AWS Lambda, Amazon S3, Amazon Bedrock, or equivalent cloud technologies is preferred. Experience developing dashboards, reports, or data visualizations using Amazon QuickSight, Power BI, Tableau, or similar BI tools. Ability to evaluate analytical and AI solutions using appropriate business and technical performance metrics. Ability to coordinate with different teams to gather business and technical requirements. Strong written and verbal communication skills with the ability to communicate analytical findings and technical concepts to senior stakeholders. Self-motivated with strong accountability, ownership, and problem-solving skills. Ability to work independently as well as collaboratively within a team. Excellent team player. Preferred / Optional Skills: Experience with Alteryx for analytics, data preparation, and workflow automation. Experience with SAS or similar statistical analytics platforms. Experience with Amazon SageMaker or other Machine Learning platforms. Experience developing Generative AI applications using Amazon Bedrock. Experience with RAG architectures, vector databases, or AI Agent frameworks. Knowledge of APIs and integration of AI/ML models with applications or business workflows. Understanding of MLOps, model deployment, model monitoring, Git, and CI/CD concepts. Experience working with unstructured data such as documents, text, images, or other multimodal datasets. Exposure to Computer Vision, multimodal AI, sensor data, robotics, simulation, or Physical AI applications is a plus. Good understanding of the US Retirement / Financial Services industry is preferred.

We are an equal opportunity employer with a commitment to diversity.  All individuals, regardless of personal characteristics, are encouraged to apply.  All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.