Data Scientist - Remote

Data Scientist - Remote 7 hours ago columbus,ohio Job Title : Data Scientist Location: Remote Job Description: Understand and prioritize business problems and identify ways to leverage data to recommend solutions to business problems. Organize and synthesize data into actionable business decisions, focused on insights. Provide insight into, trends, financial and business operations through data analysis and the development of business intelligence visuals. Collaborate with stakeholders to understand and prioritize business problems, leveraging data to recommend strategic, actionable solutions. Design, fine-tune, and optimize large language models (LLMs) and agentic AI systems, incorporating Retrieval-Augmented Generation (RAG) architectures, natural language querying over structured data, and content generation strategies. Lead research and development of cutting-edge AI techniques and evaluate emerging technologies to enhance system intelligence and autonomy. Build, scale, and optimize customer-facing machine learning workloads across industries, applying MLOps best practices to deploy and monitor models in production environments. Architect and implement multi-agent AI systems that support planning, autonomous decision-making, and adaptive execution logic. Establish responsible development frameworks and guardrails to ensure AI systems are aligned with ethical, legal, and operational standards. Architect and implement complex multi-agent systems, including planning, decision-making, and execution capabilities. Execute end-to-end data science projects, including data acquisition, feature engineering, model building, deployment, and performance monitoring. Use advanced BI tools (e.g., Tableau, Power BI) for calculations, geographic mapping, data blending, and performance-optimized data extracts. Develop and lead statistical and machine learning efforts in relation to your projects. Our projects leverage machine learning, experimentation, signal processing, time series analysis, geospatial analysis, natural language processing, and more. Partner with business stakeholders to understand their needs and translate those needs into data-driven solutions. Develop scheduling and monitoring orchestration workflows for parallel execution of jobs Utilize AWS services (EMR, EC2, S3, Athena) and GCP BigQuery for scalable cloud-based data processing Design and implement secure and efficient data pipelines to ingest and transform data from diverse platforms into AWS infrastructure. Work with a variety of relational databases, including SQL Server, MySQL, IBM DB2, and Netezza, to ensure data consistency and availability. Track development tasks and user requirements using tools like JIRA and maintain source code through IDEs and version control systems (e.g., Git). Build distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time Apply business logic to data transformation tasks using languages such as Python, R, Scala, or Java Model, design, code, test, and deploy scalable applications, integrating data science workflows into production systems. Harmonize, clean, and curate data to support analytics and modeling efforts, enabling actionable insights from raw datasets. Ensure data quality and governance by applying established frameworks, promoting consistency, and maintaining data integrity across systems. POSITION QUALIFICATIONS: Education Required: A Master’s degree in Computer Science, Analytics, Data Science, Statistics, or similar field. Required or Acceptable Job-Related Experience: 7 – 10 years related experience Technical/Other Skills Required: Strong hands-on experience in Spark, Scala, Python, R, and/or Java for developing data-intensive and AI-driven applications. Proven expertise in Amazon Web Services (AWS) big data ecosystem including EMR, Kinesis, Aurora, DynamoDB, and SageMaker; and Microsoft Azure ecosystem including Azure Databricks, Stream Analytics, Purview, and Synapse Analytics Proficient in building, training, and deploying ML/AI models using AWS SageMaker, Azure ML, Google Vertex AI, and OpenAI endpoints. Strong working knowledge of MLOps/DevOps frameworks, CI/CD pipelines, and tools such as Git, Jenkins, Maven, IntelliJ, and Eclipse to ensure scalable and maintainable deployments. Expertise in ML algorithms, statistical modeling, and data engineering best practices. Proficiency and hands-on experience in advanced analytics techniques and machine learning algorithms, including NLP, time-series analysis. Hands-on experience developing GenAI applications, including Retrieval-Augmented Generation (RAG), Text2SQL, agent frameworks, fine-tuning, and LLM deployment using tools such as HuggingFace, LangChain, OpenAI, and Google Model Garden. Experience in building production-grade ML or GenAI deployments on AWS, Azure, or GCP. Deep understanding of machine learning algorithms, statistical modeling, NLP, time series forecasting, reinforcement learning, and autonomous/agent-based systems. Experience with cutting-edge frameworks like AutoGPT, LangGraph, or CrewAI, and understanding of LLM planning, memory, and tool-use patterns in agent architectures. Demonstrated experience designing or deploying AI agents in production or advanced research settings. Strong familiarity with current debates and best practices around AI ethics, safety, and responsible development. Exceptional ability to translate complex AI/ML concepts into clear, actionable insights for both technical and non-technical stakeholders. Strong collaboration and communication skills to partner effectively with cross-functional teams including business analysts, engineers, and leadership. Proficient in producing high-quality technical documentation (design specs, test cases, and user guides) for code and model lifecycle management. Oral: Ability to collaborate and communicate with a wide range of partners, including IT and business, across all levels of the organization. Must actively manage expectations with stakeholders. Problem Solving: Must understand the business need and develop technical solutions to meet those needs. Innovation, creativity, and critical problem-solving skills are required to be successful in this role. Solutions need to be comprehensive, flexible for future changes, and delivered with a high degree of quality.