Data Science- Manager, Principal, Staff Engineers

Position: Data Science- Manager, Principal, Staff Engineers

Interview process: is 1 prescreening with PV. Then three client virtual rounds, with an extra for the manager positions. This will go fast and I can schedule multiple interviews on one day since I hold the calendars of the interview panel.

5 Exclusive Positions(Please focus on these):
1 Manager of Data Science
1 Principal Engineer of Data Science
3 Staff Engineers of Data Science

Must haves:

• GEN AI
• Time Series Experience(forecasting Models)
• Prompting and Fine Tuning
• LLM, RAG, BERT, GPT
• Appropriate Leveling- Manager needs to have manager experience, principal needs to be the top person on the team, staff needs too have at least lead experience

Job Descriptions are below for all three:

Manager:
Position Summary...

What you'll do...

Manage a team of data science and machine learning engineers to develop and deploy traditional data science and Gen AI applications supporting the Walmart finance department. Build models that

solves specific business outcome by training with massive amount of Walmart data utilizing open-source or in-house tools.

• Grow a team of domain experts of NLP, LLM , Timeseries Forecasting and recommendation systems in respective business domains in retail ; e-commerce.
• Drive execution of developing models and systems
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Remain up to date on ongoing research and development activities in the team
• Work with data scientists to design, architect, and build AI/ML/DL model and model systems.
• Work with machine learning engineers to deploy, operate, and optimize scalable solutions

About the Team: Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, Walmart U.S. offers an extensive selection that our customers value, whether they shop online at Walmart.com, through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.

What you'll bring:

• Experience in NLP, LLM, Timeseries, Traditional ML techniques
• Experience in data science and machine learningfor retail ; e-commerce
• Experience in managing a mid-size internal team of data scientists and MLEs
• Experience leading and completing cross-functional projects
• Strong organizational skills including prioritizing, scheduling, time management, and meeting deadlines
• Strong influencing and interpersonal skills
• Detail and results-oriented with sense of urgency

Principal
What You'll Do

• Develop LLM-powered intelligent experiences that interpret and generate insightsfrom both tabular and unstructured data.
• Build and optimize personalized Q&A systems using large language models, enabling context-aware responses tailored to user needs.
• Design and enhance conversational talent recommendation systems, combining autonomous agent architectures with personalized recommendation algorithms.
• Advance traditional recommendation systems by evolving them from simple ranked lists to multi-topic, interactive experiences that better reflect user intent.
• Construct multi-agent intelligent workflows that translate natural language inputs into complex, goal-directed task sequences.
• Collaborate within a highly cross-functional team, including data scientists, machine learning engineers, product managers, and UX designers.
• Partner with fellow data scientists to design, prototype, and iterate on AI/ML models and system architectures.
• Work closely with machine learning engineers to deploy, monitor, and optimize scalable AI/ML solutions in production environments.
• Collaborate with product managers to design intuitive user experiences, define feedback loops, and analyze user telemetry to guide product improvements.
• Engage in end-to-end AI/ML product development, from ideation to deployment, while continually expanding your technical and product skillset.
• Follow and help define robust development standards to ensure the creation of trustworthy, safe, and responsible AI systems.
• Contribute to internal and external AI/ML research through experimentation, whitepapers, and collaboration with the broader AI community. What You'll Bring Proven experience deploying high risk NLP applications in real-world, production environments-such as those involving regulatory compliance, privacy, safety, or fairness.
• Demonstrated ability to advance and implement Trustworthy AI and Responsible ML practices, working cross-functionally with engineering, legal, policy, and product stakeholders across a large enterprise.
• Track record of mentoring and coaching junior data scientists, especially in navigating ambiguous or novel problem spaces. Strong applied machine learning experience, with solid foundational knowledge in statistics, optimization, and deep learning-preferably gained at leading technology companies (e.g., Google, Meta, Microsoft) or AI-first startups.
• Excellent communication skills with the ability to synthesize complex technical work into accessible insights for executive briefings, research publications, and external presentations.
• Advanced proficiency in Python and common ML/DS libraries such as NumPy, pandas, scikit-learn, as well as deep learning frameworks like TensorFlow, PyTorch.
• Experience designing and deploying scalable deep learning systems, including neural network architecture optimization, model distillation, quantization, or on- device inference.
• Strong understanding of machine learning infrastructure, including experience with Kubeflow, MLflow, Airflow is a plus.

Bonus Skills:

• Hands-on experience with Text-to-SQL or Text-to-Cypher based application, or the design of modern recommender systems.
• Experience developing or fine-tuning large language models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), or open-weight model
  customization.
• Publication history in top-tier ML/NLP conferences such as NeurIPS, ICML, ACL,EMNLP, or ICLR

Staff:
What you'll do...

Chance to work on financial data for complex problems/challenges. Utilize LLMs/Genai systems and architectures to build and deploy state-of-the-art Genai systems. Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting-edge data-driven solutions. We specialize in a range of initiatives which provides actionable insights into trends and patterns and leveraging Generative AI (Genai) to produce concise, insightful summaries that empower decision-makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations.

About Team:
Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, Walmart U.S. offers an extensive selection that our customers value, whether they shop online at Walmart.com, through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.

What you'll do:

• Lead high-caliber team to build large-scale Genai systems
• Develop data science systems and tools for retail; e-commerce applications:
• Leverage LLMS to summarize and build large scale applications
• Establish cross-functional relationships to maintain win-win situation for the corporation
• Collaborate with various product stake holders and business owners to formulate and productionize a solution.

What you'll bring:

• Master's degree or PHD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in analytics related field.

Must have qualifications...

• Strong solution architecture mindset, with the ability to apply AI/ML technologies to solve complex business problems.
• Experience with training and inference of large-scale AI models such as Large Language Models (LLMs), multimodal models, and reasoning models.
• Knowledge of advanced model optimization techniques, including quantization, pruning, distillation, Low-Rank Adaptation (Lora), and Parameter-Efficient Fine-Tuning (PEFT) for cloud deployment.
• Solid understanding of LLMs and Genai ecosystems, including GPT, LLaMA, Mistral, Claude, Gemini, AWS Sonnet, and related frameworks/tools.
• Hands-on experience with RAG (Retrieval-Augmented Generation), AI agent development, and frameworks such as Lang Chain, Langgraph etc.,

Great to have...

• Experience with Big Data processing and feature engineering using Spark
• Experience with training machine learning models through Cloud Services including Google Cloud Platform and Microsoft Azure
• Hands on experience of designing and training large DL models on GPU

Behavior qualifications:

• Problem solver with can-do attitude, not afraid of facing new problems, technical challenges, delivery pressures
• Ability to clearly define problems, models and constraints from informal and flexible business requirements
• Tech leadership with teamwork spirit, quick adaptation to new environment
• Form collaborative working environment.
• Demonstrated ability to manage multiple cross-functional initiatives, balancing competing priorities and deadlines.
• Comfortable working in ambiguous, rapidly changing environments, with strong problem-solving and adaptability.
• Highly motivated to demystify emerging technologies and drive adoption across teams and stakeholders.