Principal Data Scientist

Key Skills

Amazon RedShift, Continuous Integration & Continuous Delivery - CI/CD, Data Analysis, Data Architecture, Data pipelines, Database, GraphQL, Machine learning techniques, MLOps tools, OLAP, OpenCV, PySpark, Python Programming, Snowflake, SQL

Job Description

Atyeti is looking for a principle data scientist to help build and lead our teams throughout the regulatory technology space for our financial services clients. Regulatory Technology is a growing sector, core to our business and ensures regulatory compliance through data analysis across global jurisdictions. Currently we have several teams transitioning from on-prem to cloud, including massive refactoring efforts and adoption of new tools, workflows, and team structures. This is a pivotal leadership roll requiring you to provide on-the-ground leadership to teams as well as thought leadership to both Atyeti and our clients.

What You’ll Do:

• Provide hands on guidance to several teams, help educate and skill up on new tooling and technologies
• Mentor Associate and Senior level data professionals and support their advancement
• Play a key role in migration to a best-practices cloud infrastructure on Azure using multiple data platforms
• Ensure quality development and analytics through code and analytic reviews
• Provide Solution Architecture services and draft technical requirements to new projects and assist in team building
• Work with machine learning engineers to help craft appropriate and effective solutions
• Help build our company-wide data science community with weekly meetings, events, presentations and general knowledge sharing.
• Work with data engineers to ensure robust, maintainable data pipelines are designed which conform to company standards of data validation and data providence, meet performance requirements and operate efficiently
• Provide technical support and guidance to day-to-day team members, such as BA/PMs and product owners, to ensure long term progress and success

Qualifications

What You Have:

• Strong python programming experience at a Lead Developer level (application development, CI/CD)
• 8-15 years total experience with 5+ years experience leading a data science team to include: data engineering, data analysis, machine learning and data visualization
• Excellent skills communicating deep learning topics with non-technical stake holders
• Experience in data science project planning, orchestration, code and analytic reviews
• History of managing several major projects from planning to deployment using microservices or serverless architecture
• Strong background in statistics and ML concepts, including proper support for accuracy evaluation, proper testing procedure and ground truth establishment, Bayesian Statistics, distribution testing
• Experience in cloud architecture around batch and stream pipelines, MLOps, model deployment
• Knowledge of various data set types including document, relational, graph, and timeseries
• Expert level SQL and Regex
• Large scale experience (>10^10 rows, 1k+ compute nodes, >10^8 documents)
• Pytorch, Pyspark at scale (development and optimization), Tesseract, distributed OLAP databases (Redshift, Snowflake, etc), ML libraries such as sklearn
• Experience with software development outside of python (.net, web programming)
• Data extraction experience (OCR, Web Scraping)
• Computer vision experience (OpenCV, CNN)