Hey Folks,
Please share quality resumes for the below mentioned JD in my mail id mentioned below.
Email is the best way to reach me.
NOTE: F2F INTERVIEW MANDATORY.
Location: Cincinnati, OH (Need local) (F2F interview)
Visa: USC, GC-EAD, H4-EAD, L2S AND TN Only
Client: Kroger
Requirements:
• 6+ years of experience as a Data Scientist or ML Engineer
• High level of independence in developing and owning toolkits, pipelines, models, and dashboards
• Experience designing, building, and deploying scalable cloud-based solution architectures
• Proficiency with public cloud platforms like AWS, Azure, or GCP
• Experience with MLOps, CI/CD pipelines, and TDD/BDD practices
• Extensive knowledge of machine learning frameworks, libraries, data structures, data modeling, and software architecture
• In-depth knowledge of mathematics, statistics, and algorithms
• Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes)
• Strong programming skills in one or more languages, such as Python, Java, Go, JavaScript, or C++
• Familiarity with infrastructure components like storage and networking
• Strong analytical problem-solving skills
• Excellent written and verbal communication skills
• Self-starter with initiative, able to perform well under pressure
• Business-minded approach to managing time, costs, and milestones
• Ability to work effectively within a matrixed team environment
Nice to Have:
• Microsoft Certified: Azure Data Scientist Associate (DP-100)
• Experience with Azure Service Fabric, Azure Databricks, Power BI, Azure ML, or Azure Synapse
• Experience with combinatorial optimization
• Experience with GitHub Functions
• Experience with SQL Server, SSIS, ETL/ELT, NoSQL, Redis, ODS
• Familiarity with industry-standard data models such as ADRM or Common Data Model
• Experience with Domain-Driven Design, microservices, Event-Driven and Mesh App architectures
• Experience in the Retail industry
Typical Duties:
• Collaborate with solution architects, data scientists, and product managers to iterate on the design and implementation of Fulfillment Services Data Strategy
• Act as a technical advisor and troubleshoot technical challenges with data product infrastructure and applications
• Design and develop machine learning and deep learning systems
• Conduct machine learning tests and experiments
• Implement appropriate machine learning algorithms
• Transform data science prototypes into production models, applying appropriate ML algorithms and tools
• Document the machine learning process for transparency and knowledge sharing
• Create data pipelines for various streaming use cases
• Ensure data quality and focus on enhancing the overall product’s user experience
• Establish standards, processes, and procedures for optimal results
• Manage individual project priorities, deadlines, and deliverables
• Assist the scrum master by creating technical stories and spikes
• Adapt quickly to evolving technology and business requirements
• Stay up to date on emerging technologies within the company and the industry
Best Regards,
Vanshika – Sr. IT Recruiter
Stawn Consulting