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.
