JOB-11360 - Calsoft Labs

Job Description:

*** is on a mission to build the best instore and online grocery shopping experience, competing against the best in e-commerce. Our goal is to connect customers with the most comprehensive assortment of quality products in the most convenient ways. As part of this mission, we want to build a robust fulfillment service to assist our employees working at stores and distribution centers, satisfy customer orders in an accurate and timely manner, irrelevant of the ordering channel and delivery mechanisms. This includes innovations and efficiencies leveraging technologies such as robotics, artificial intelligence, machine learning, voice assist etc. Efficiencies and accuracy in fulfilling orders will allow *** to offer its customers competitive pricing and a great customer experience.

As an Data Scientist, you will have the opportunity to support a team of mixed-skill Engineers that have a direct and meaningful impact on the *** Fulfillment Services Platform roadmap. You will evaluate existing machine learning (ML) processes, perform statistical analysis to resolve data set problems, and improve the accuracy of our ML models. You will assist in design & implementation of cloud-native, well-architected solutions that integrate well into the existing *** systems. You will also provide best practices on secure foundational cloud implementations, automated provisioning of infrastructure and applications, cloud-ready application architectures, and more. You will strive to continuously improve the software delivery processes & practices and be a role model to other engineers from application teams.
You will join an innovative, distributed Software Delivery team within the US's largest grocery retailer with a scale that reaches millions of people every day. Our teams are truly agile and empowered to own all aspects of their domain comprehensively. We encourage a culture of quality software practices and respect for the human spirit. We are committed to being an inclusive and transparent culture cultivating the best engineers, allowing them to define our *** Technology platforms' future. If this inspires you, apply and talk to our team!

REQUIREMENTS
" Experience designing, building, and deploying scalable cloud-based solution architectures
" Experience working with public cloud platforms such as AWS, Azure. GCP
" Experience in MLOps, CI/CD, TDD/BDD
" Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
" In-depth knowledge of mathematics, statistics, and algorithms.
" Knowledge of containerization and container orchestration technologies.
" Good understanding and/or experience writing software in one or more languages, such as Python, Java, Go, JavaScript, C++, or similar
" Familiarity and good understanding of infrastructure storage, networking etc.
" Strong analytical problem-solving skills
" Excellent written and verbal communication skills
" Self-starter takes the initiative and works well under pressure
" Business-minded approach to time, costs, and milestones
" Can work well within a matrixed team environment


MINIMUM QUALIFICATION/EDUCATION
" 5+ years experience as a Data Scientist/ML Engineer.
" High level of independence to develop and own toolkits, pipelines, models and dashboards.

BONUS POINTS
Microsoft Certified: Azure Data Scientist Associate (DP-100)
Experience with Azure Service Fabric, Azure Databricks, Power BI, Azure ML, Azure Synapse
Experience with combinatorial optimization
Experience with GitHub Functions
Experience with SQL Server, SSIS, ETL/ELT, NoSQL, redis, ODS
Experience working with Industry Standard Data Models such as ADRM, Common Data Model
Experience in Domain Driven Design, microservices, Event Driven and Mesh App
Experience in Retail industry

Key Responsibilities:

" Collaborate with solution architects, data scientists & product managers to iterate on the design & implementation of Fulfillment Services Data Strategy
" Be a technical advisor and troubleshoot to resolve technical challenges with data product related infrastructure and application(s)
" Design and develop machine learning and deep learning systems
" Run machine learning tests and experiments
" Implement appropriate ML algorithms
" Transform data science prototypes and apply appropriate ML algorithms and tools
" Document machine learning process
" Create data pipelines for various types of streaming use cases
" Focus on overall product s data quality and user experience
" Build standards, processes and procedures to deliver best results
" Manage individual project priorities, deadlines, and deliverables
" Assist the scrum master in creating technical stories/spikes
" Adapt quickly to changing technology and business requirements
" Stay up to date on emerging technologies across *** and the industry