Principal Data Scientist - Applied AI

Principal Data Scientist - Applied AI at Sigmoid Principal Data Scientist - Applied AI at Sigmoid in Stone Park, Illinois Posted in about 21 hours ago.

Type:

full-time

Job Description:

About Sigmoid Analytics:

Sigmoid unlocks business value for Fortune 1000 companies through expert data engineering, data science, and AI consulting. We solve complex challenges for leaders in CPG, Retail, BFSI, and Life Sciences. With 10+ delivery centers in the USA, Canada, UK, Europe, Singapore, and India, we deliver cutting-edge data modernization and generative AI solutions. Join us to shape the future of data-driven innovation! Why Sigmoid? Inc. 500 Fastest-Growing Companies (4 years running) Deloitte Technology Fast 500 (4 years running)

Top Employer:

AIM's 50 Best Firms for Data Scientists Recently named British Data Awards Finalist & more accolades on the way! Accelerate your career with a fast-growing, innovative company. Apply now and be part of our award-winning team!

Summary:

The role is expected to serve as the primary client-facing data science lead to design, build, and scale advanced AI and machine learning solutions for enterprise clients. This role combines strong hands-on expertise in generative AI, NLP, machine learning, and data engineering with consulting maturity, stakeholder management, and solution ownership. The position emphasizes a mix of client advisory, model development, cross-functional collaboration, and measurable business impact

Desired Experience :

8 - 12 years of experience in data science, machine learning, analytics, or applied AI roles. Demonstrated experience leading teams or technical workstreams in enterprise environments. Experience building and deploying Gen AI, NLP, or advanced machine learning solutions in production settings. Exposure to client-facing consulting, solutioning, stakeholder management, or external business engagements. Strong problem-solving ability with a track record of delivering measurable business outcomes

Role & Responsibilities :

Design, develop, and deploy advanced AI/ML solutions, including generative AI applications, RAG systems, NLP pipelines, and predictive models. Translate ambiguous business requirements into structured analytical approaches, technical architectures, and scalable solution roadmaps. Lead technical workstreams and collaborate with data scientists, data engineers, product managers, and business teams to deliver end-to-end solutions. Partner with client stakeholders to identify high-value AI use cases aligned to business priorities and bring thought leadership to the way AI systems are designed Present solution concepts, prototypes, analyses, and business outcomes to senior client and internal stakeholders. Support presales activities through solution framing, technical proposals, demos, and effort estimation for AI and data science opportunities. Build and optimize production-grade AI pipelines using modern cloud, vector search, and data platform technologies. Provide technical mentorship to junior team members and contribute to capability building through reusable accelerators, best practices, and thought leadership Primary Skills (Mandatory) Strong expertise in Generative AI, LLMs, RAG frameworks, agentic workflows, NLP, embeddings, transformers & deep learning. Proficiency in Python, PySpark, SQL, and modern machine learning libraries such as PyTorch, Transformers, scikit-learn, LangChain, and LangGraph. Experience with cloud and data platforms such as Snowflake, BigQuery, PostgreSQL, Redshift, Azure AI Search, and vector databases. Ability to architect scalable AI systems that integrate structured and unstructured enterprise data. Experience in creating knowledge layers, semantic search, or enterprise copilots. Exposure to model fine-tuning, evaluation frameworks, guardrails, and LLM governance Strong communication skills with the ability to articulate technical concepts and business value to senior stakeholders Preferred Education background Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Engineering, Operations Research, or a related discipline