Senior Data Scientist Consultant, SPI – Agent Platform Team

Summary

The Agent Platform Team, within AI Enablement at 84.51°, owns and manages the core platforms that power data science and AI across the organization. This role sits on the SPI (Science Platform Innovation) squad and is focused specifically on the Databricks environment and its evolving AI/ML capabilities.

You will be the bridge between the engineers building and maintaining our Databricks platform and the data scientists who use it every day. You are not building models for end-clients. Instead, you ensure the platform behaves as expected for the people on it—that new capabilities are tested, documented, and adopted smoothly, and that practitioner pain points make it back to the platform team in a way that shapes the roadmap.

You’ll build deep familiarity with Databricks’ infrastructure and AI powered capabilities —including Genie Code, Genie spaces, Agent Bricks, MLflow, and other features as they emerge—as well as the Unity Catalog governance layer that underpins them. You’ll test and evaluate new Databricks features and relevant third-party integrations from the perspective of an end-user, document your findings, and help the team decide what to adopt, how to roll it out, and what to skip.

This is a small, highly collaborative squad. Everyone pitches in on a bit of everything. Priorities shift frequently as the Databricks roadmap evolves. Success in this role is less about fixed technical expertise and more about comfort with ambiguity, good judgment about where to spend your time, and the ability to influence without direct authority.

Responsibilities

• Voice of the practitioner: Serve as the primary liaison between data scientists using Databricks and the platform engineering team. Gather requirements, surface pain points, and translate practitioner needs into actionable feedback that shapes platform decisions and roadmaps.
• Technology evaluation: Lead the testing and evaluation of new Databricks capabilities (e.g., Mosaic AI features, Model Serving enhancements, Genie, new Unity Catalog functionality) and relevant third-party tools. Document findings, recommended use cases, limitations, and rollout considerations. Over time, this may evolve from hands-on beta testing toward designing and coordinating evaluation efforts across groups of practitioners.
• Onboarding & enablement: Write guides, maintain documentation, lead training sessions, and run office hours to help data scientists adopt new platform capabilities. Partner with Learning & Development where appropriate. Serve as a first line of support when teams hit roadblocks.
• Adoption & communication: Evangelize Databricks capabilities to increase awareness and drive adoption. Produce clear release notes, communications, and materials for both technical and non-technical audiences.
• Cross-functional collaboration: Work closely with the solution architect, cloud engineer, and product senior on the squad to ensure proposed technologies have well-defined use cases and that guidelines and best practices are established. Act as a data science ambassador to cross-functional teams, explaining recommended workflows and the reasoning behind platform choices.
• Governance & compliance support: Help validate that new platform capabilities meet enterprise requirements around security, compliance, observability, and data governance (e.g., Unity Catalog lineage, Azure connectivity).

Qualifications & Experience

• Bachelor’s degree in mathematics, statistics, computer science, economics, or a related discipline.
• 2–4 years of experience in data science, AI/ML development, or applied analytics.
• 2–4 years of experience in tech consulting, retail analytics, or related professional services.
• Hands-on experience with Python, SQL, PySpark and Databricks
• Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams.
• Experience partnering with software engineering and/or product management teams.
• Familiarity with LLMs, prompt engineering, or agentic AI concepts is a strong plus.
• Experience with the Databricks ecosystem (Unity Catalog, MLflow) is a strong plus.
• Exposure to agent frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) is a plus.

Skills

• Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation.
• Ability to influence across teams and seniority levels without direct authority.
• Comfort operating in ambiguity—priorities shift frequently, and you need good instincts about where to focus.
• Strong project and time management skills; able to manage multiple priorities with minimal oversight.
• Curiosity and enthusiasm for emerging AI technologies and a genuine desire to become a subject matter expert on the Databricks platform and its AI capabilities.

#LI-SSS

Senior Data Scientist / P3358

Summary

We are seeking a Senior Data Scientist to join our Proprietary Models team. In this role, you will play a critical part in developing, evaluating, and democratizing our foundation models portfolio—including embeddings, pre-trained LLMs, and fine-tuned language models. You will build and optimize embedding pipelines, design rigorous evaluation frameworks, drive models from experimentation to production, and guide business stakeholders through the process of integrating these models into their workflows. The ideal candidate combines deep technical expertise in machine learning and AI with strong problem-solving abilities, a commitment to engineering excellence, and a passion for enabling others to leverage AI effectively.

Responsibilities

Your work will cover a lot of ground, from engineering data pipelines to testing novel AI methodologies to guiding business stakeholders. You will be expected to flex between these skill domains as work progresses through its lifecycle, and to collaborate within a team to make it all happen.

• Develop and optimize embedding pipelines for vector search, retrieval-augmented generation (RAG), and downstream ML applications.
• Conduct rigorous model testing, evaluation, and validation against quality metrics, performance benchmarks, and reliability standards prior to release.
• Design and execute proof of concepts to demonstrate feasibility for specific business problems.
• Build and maintain automated testing frameworks for model performance, data quality, and pipeline integrity.
• Collaborate with MLE/Researchers/Engineers to develop, fine-tune, and deploy foundation models.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing to support model development.
• Develop and maintain Jupyter notebooks, scripts, and workflows for reproducible experimentation and analysis.
• Contribute to building and maintenance of code packages, APIs, hosted applications, and other foundation model delivery mechanisms.
• Troubleshoot integration challenges and provide technical guidance for model integrations.
• Guide business stakeholders, data science and engineering teams through adoption and integration of foundation embedding and generative AI models.
• Create documentation, user guides, and best practices for internal model adoption and usage.
• Serve as a liaison between the Foundation Models team and business stakeholders, gathering feedback to inform the development roadmap.

Qualifications and Experience

Required

• Bachelor’s degree in Data Science, ML, Computer Science, or a related discipline
• 3+ years of hands-on experience in data science or machine learning roles
• 3+ years’ experience building in Python using big data tools (e.g. Hadoop, Databricks)
• Hands-on experience building processes incorporating LLMs, embeddings, or related model architecture
• Experience applying embeddings within AI projects and machine learning applications
• Track record of shipping, measuring, and maintaining machine learning models in production
• Exceptional communication skills with ability to explain complex technical concepts to non-technical audiences
• Experience in stakeholder management, technical documentation creation, and cross-functional collaboration

Preferred

• Experience building in cloud data platforms (i.e. Azure, GCP)
• Previous developer relations, technical evangelism, or advocacy experience
• Background in NLP, conversational AI, or generative AI applications
• Open-source contributions or thought leadership in AI/ML community

#LI-SSS

DIRECTOR, DATA SCIENCE - SUPPLY CHAIN, OPERATIONS, REPLENISHMENT

Cincinnati, OH

Chicago, IL

SUMMARY:

The Supply Chain, Operations, and Replenishment  (SCORe) team is responsible for creating for cutting edge supply chain and operations sciences to meet Kroger’s need now and in the future, ensuring that we deliver value for our Kroger stakeholders and the enterprise.  This role will lead the supply chain data scientists and partner heavily with our Product and Engineering community to develop the best solutions for our stakeholders within our supply chain workstreams.

RESPONSIBILITIES:

• Influence and partner with SCORe team leaders to set the vision and future road map by developing immediate and long-term strategic plans in supply chain and operations
• Partner with the other SCORe Tech DSR Leads to develop and oversee innovation/capability roadmaps to support strategic supply chainplans
• Bring transformational, innovative thinking to the SCORe team, creating and/or improving ways of working, products, sciences, tools and initiatives
• Develop and manage stakeholder relationships within 84.51° and Kroger to drive better decisions across the Supply Chain space
• Understand business priorities and project value to make prioritization decisions
• Partner with cross-functional leaders to ensure shared goals that enable delivery of science services and insights at scale
• Enable & manage a team of data scientists in delivering strategic objectives and work plans while developing their individual technical and business skills

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 7+ years developing analytical solutions using advanced AI, Machine learning, and optimization methods
• 7+ years querying data from relational databases using SQL/Python to develop analytical solutions
• 7+ years with data wrangling, data cleaning and prep, problem framing, and analysis
• Experience with managing, recruiting, training, developing, coaching, and/or inspiring highly technical associates
• Proficient in technology stack (Azure, Databricks, Python, Spark)

• Experience applying data science capabilities to supply chain and operations business problems

• Experience with developing, coaching, and/or inspiring highly technical associates
• Ability to work in a highly collaborative cross functional environment
• Comfort with fast pace and multiple moving parts, anticipating and solving for future barriers/ changes 
• Excellent interpersonal, collaboration, and communication skills
• Strong business acumen
• Strong academic background in mathematics, statistics, computer science, economics, or similar discipline
• Strong analytical, creative problem-solving and decision-making skills
• Ability to create computationally efficient solutions
• Natural curiosity and passion around data, analysis and insights
• Welcomes and embraces change
• Ability to work fast yet accurately
• An openness and willingness to try new things and to fail 

An ideal candidate has a strong track record of: 

• Building stakeholder relationships at a senior level
• Internal or External client exposure and strong understanding of client’s business needs
• Ability to present technical solutions to non-technical audience
• Managing, recruiting, training, developing, coaching, inspiring and/or leading others
• Championing an inclusive culture and embracing 84.51° D&I initiatives 
• Creating and/or improving large-scale processes or initiatives
• Leading Data Scientists through product life cycle and projects
• Independently creating solutions and solving open-ended and/or complex problems, analyzing both successes and failures
• Collaborating across all functions of 84.51° 
• Providing direct, constructive feedback to peers and junior data scientists 
• Making data-driven decisions and priority calls
• Clearly articulating their point-of-view
• Comfortability with fast pace and multiple moving parts, anticipating and solving for future barriers/ changes 

#LI-SSS

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Define project requirements by identifying project milestones, phases, and deliverables
• Execute project plan, report progress, identify and resolve problems, and recommend further actions
• Delegate tasks to appropriate resources as project requirements dictate
• Design, develop, and deliver audience training and adoption methods and materials

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Databricks and DBT experience is a plus
• Experience building and optimizing data pipelines, architectures, and data sets
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytic skills related to working with structured and unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets
• Ability to interface with multiple other business functions (internally and externally)
• Desire to build analytical competencies in others within the business
• Curiosity to ask questions and challenge the status quo
• Creativity to devise out-of-the-box solutions
• Ability to travel as needed to meet client requirements

• Competitive pay and bonus
• Travel incentive bonus structure
• Flexible time off
• Investment in your growth and development
• Full health, vision, dental and life benefits
• Paid parental leave
• 3:1 charity match

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Define project requirements by identifying project milestones, phases, and deliverables
• Execute project plan, report progress, identify and resolve problems, and recommend further actions
• Delegate tasks to appropriate resources as project requirements dictate
• Design, develop, and deliver audience training and adoption methods and materials

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Databricks and DBT experience is a plus
• Experience building and optimizing data pipelines, architectures, and data sets
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytic skills related to working with structured and unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets
• Ability to interface with multiple other business functions (internally and externally)
• Desire to build analytical competencies in others within the business
• Curiosity to ask questions and challenge the status quo
• Creativity to devise out-of-the-box solutions
• Ability to travel as needed to meet client requirements

• Competitive pay and bonus
• Travel incentive bonus structure
• Flexible time off
• Investment in your growth and development
• Full health, vision, dental, and life benefits 
• Paid parental leave
• 3:1 charity match

WHAT WE DO

Our Data and Analytics consultants work with clients at all levels of the organization, from the C-suite to the shop floor, helping them to deliver on their most strategic initiatives. We’re known for making realistic, data-driven decisions that deliver value in tangible ways to our clients. Our clients ask for us on projects that require a superior combination of technical and business capabilities, people and management skills, and a collaborative mindset. We excel in understanding complex programs and strategic initiatives and breaking them into actionable pieces.

We are actively looking for professionals in the following areas:

• Data Strategy
• Data Governance
• Data Modernization
• Advanced Analytics
• Data Visualization

The ideal candidate’s experience may include but is not limited to the following:

• Have experience understanding and solving real business problems
• Have experience with presenting business case and strategy to the C-Suite
• Bring industry domain knowledge for custom data and analytics strategies
• Experience in designing and implementing data driven products and services
• Experience in designing and building high performance collaborative business and technology teams that deliver high value data solutions, data products and data analytics

Ideal candidates may call themselves Data Architects, Data Engineers, Data Scientists, Analysts and Data Governance professionals. Experience may include but not limited to the following:  

Data Strategy and Governance

• Intimately familiar with data technologies, data architecture frameworks, cloud platforms and the emerging trends in technological advancements.
• Proven experience in transforming our clients from on-prem data platforms to the cloud.
• Lead data modernization initiatives that include platform, technology and tools implementation and adoption.
• Must have experience in architecting and implementing data architecture, data engineering, reporting and analytical solutions across multiple business functions and domains.
• Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
• Demonstrate a rigorous and analytical problem-solving approach, leading information-gathering sessions and preparing and delivering client presentations and work products/prototypes.
• Identify data governance gaps and assess data governance maturity in a complex data environment. Should also be able to Identify the implications for data governance that arise from the technology, current processes, and skill levels in a complex data environment.

Data Architecture and Engineering

• Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing.
• Experience designing and building data platforms that support data lakes, data stores, data ingestion and transformations and API services for consuming data
• Ability to design and build complex data pipelines that either stream data in
• Experience and knowledge of programming and scripting languages, such as but not limited to Python, Node.JS and SQL
• Experience and knowledge of data integration tools and platforms
• Experience and knowledge of relational and dimensional database structures, theories, principles, and practice used in data warehousing and analytics solutions
• Ability to design and build data models using the appropriate technics to meet business objectives
• In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies.

Advanced Analytics and Data Visualizations

• Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire
• Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods
• Experience and knowledge of programming and scripting languages such as, but not limited to, SQL, Python and R
• Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep
• Experience and knowledge of relational and dimensional database structures, theories, principles, and practice used in data warehousing and analytics solutions
• Experience deploying enterprise-wide reporting solutions while leveraging data visualization best practices

A career at SEI extends well beyond providing great service and thought leadership to our clients. Everyone takes an active role in building and managing our business, in an environment that runs counter to traditional consulting firms. Our consultants have a “seat at the table” and contribute to growing our business in ways that align to their interests such as growing business development opportunities, conducting interviews to support our hiring process, managing internal initiatives that build our brand or organizing trainings to share what you know with your colleagues. There is no telling what an SEI Consultant will be asked to do on a day-to-day basis – we do what it takes to get the job done.

QUALIFICATIONS

Required-

• Alignment to our core values: Excellence, Participation, Integrity and Collaboration
• Hungry, Humble, Smart
• Demonstrated business and technology acumen
• Strong written and verbal communication skills
• Understanding and experience solving real business problems
• Proven track record of delivering results
• Experience working with and/or leading a team
• Ability to work across industries, roles, functions & technologies
• Authorization for permanent employment in the United States (this position is not eligible for immigration sponsorship)

Preferred-

• Bachelor’s degree
• 8+ years professional experience
• Experience across our service offerings