As a Staff Data Scientist responsible for building scalable end-to-end data science solutions for our data products.
Work closely with data engineers and data analysts to help build ML- and statistics-driven data quality and continuous data monitoring workflows
Solve business problems by scaling advanced Machine Learning algorithms and complex statistical models on large volumes of data
Own the MLOps lifecycle, from data monitoring to refactoring data science code to building robust model monitoring workflows for model lifecycle management
Demonstrate strong thought-leadership and consult with product and business stakeholders to build, scale and deploy holistic machine learning solutions after successful prototyping.
Follow industry best practices, stay up to date with and extend the state of the art in machine learning research and practice and drive innovation
Promoteand support company policies, procedures, mission, values, and standards of ethics and integrity.
What you'll bring: Preferredqualifications:
Knowledge of the foundations of machine learning and statistics
Solid Experience working on Gen AI Techstack and building Gen AI powe'red solutions in production
Experience withweb service standards and related patterns (REST,gRPC)
Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind
Familiar with distributed in-memory computing technologies
Solid experience working with state-of-the-art supervised and unsupervised machine learning algorithms on real-world problems
Strong Python coding and package development skills
Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and MapReduce;Ability to work in a big data ecosystem - expert in SQL/Hive and ability to work with Spark.
Able to refactordata science code andhas collaborated with data scientists in developing ML solutions.
Experience playing the role of full-stack data scientist and taking solutions to production.
Experience developing proper metrics instrumentation in software components, to help facilitate real-time and remote troubleshooting/performance monitoring.
Educational qualifications should be preferably in Computer Science, Statistics,Engineeringor a related area.
Good effective communication (both written and verbal) skills and the ability to present complex ideas in a clear ; concise way, to different audiences. Ateam player with good work ethics
Preferred prior experience in Retail, Risk and Fraud Detection
Require mandatory hands on experience in working in Spark or other comparable distributed computing frameworks
Minimum Qualifications...
Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years experience in an analytics related field. Option 3: 6 years experience in an analytics or related field.
Job Classification
Industry: RetailFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full time