UiPath RPA Developer: Automate Finance & Supply Chain

TechDigital Group; St. Louis (MO); On-site; USD 60,000 - 100,000; Full time

Job summary

An innovative firm is seeking a skilled RPA Developer to create and enhance automation solutions using UiPath. This role involves migrating existing automations from Blue Prism and streamlining manual tasks across various applications like PeopleSoft. The ideal candidate will have a strong proficiency in UiPath, basic coding skills in C# and SQL, and the ability to work collaboratively in a team environment. Join a dynamic team where your contributions will help optimize finance and supply chain processes, making a significant impact on operational efficiency.

Qualifications

• Proficiency in UiPath is mandatory for this role.
• Basic coding skills in C# and SQL are required.

Responsibilities

• Develop and implement RPA solutions using UiPath.
• Migrate automations from Blue Prism to UiPath.

Skills

UiPath

Blue Prism

C#

SQL

Teamwork

Education

High School Diploma

College Degree

Tools

UiPath

Blue Prism

Job description

Note: Client are looking for candidates with strong Python-based data science and machine learning experience, combined with hands-on exposure to modern AI/LLM frameworks and agentic AI development on Cloudera / Databricks.

Job Description:
In this role, you will :-
• Join Marketing Services Technology team to develop analytical frameworks and reliable measurement strategies for various products, services, and capabilities.
• Design, execute, and analyze complex business and user experiments
• Partner with Product partners and other Data Engineers to set the vision and develop experimentation specifically focused on Profiling Engine, Advanced Segmentation Engine and Advanced Targeting.
• Communicate key insights from analyses, experiments, and data products to stakeholders
All About you :-
Core Data Science & Analytics

• Demonstrate strong expertise in data exploration, feature engineering, statistical modeling, and predictive analytics, with the ability to operationalize models in production environments.
• Have deep proficiency in Python (preferred) and/or R, with experience using modern data science libraries such as NumPy, Pandas, Scikit-learn, and PyTorch or TensorFlow.
• Be highly proficient in SQL and experienced in working with large-scale data warehouses and data pipelines.

Machine Learning & AI Engineering

• Possess strong experience developing, evaluating, and deploying machine learning and deep learning models across the model lifecycle.
• Experience building and deploying models using modern ML and MLOps practices, including experiment tracking, model versioning, CI/CD for ML, and monitoring.
• Familiarity with cloud-based ML platforms (AWS preferred) and distributed data processing frameworks (e.g., Spark).

Generative AI & Agentic Systems

• Hands-on experience with Large Language Models (LLMs) and Generative AI frameworks, including prompt engineering, retrieval-augmented generation (RAG), and model orchestration.
• Experience building AI agents or agentic workflows capable of reasoning, tool use, multi-step task execution, and autonomous decision-making.
• Familiarity with LLM application frameworks (e.g., LangChain, LlamaIndex, or similar orchestration frameworks).
• Experience with vector databases, embeddings, and semantic search for building knowledge-driven AI systems.

Agentic Coding & AI-Assisted Development

• Strong understanding of AI-assisted software development workflows, including agent-based coding, code generation, automated debugging, and evaluation loops.
• Experience integrating LLMs with APIs, internal tools, and data systems to build production-grade AI copilots or autonomous workflows.

Business Impact & Communication

• Ability to translate complex technical concepts into clear business insights, communicating effectively with both technical and non-technical stakeholders.
• Strong analytical thinking with the ability to work with ambiguous or incomplete data, develop creative analytical approaches, and connect results to business outcomes.

Domain & Collaboration

• Experience applying data science in digital marketing, customer analytics, or growth analytics is highly desirable but not mandatory.
• Comfortable collaborating with engineering, product, and business teams to build scalable data products and AI-driven solutions.