Lead Data Scientist

Key Skills

Amazon RedShift, Data Analysis, Data Architecture, Data science techniques, Data Visualization, Deep Learning, Effective communication skills, Machine learning techniques, OLAP, PySpark, PyTorch, Snowflake, SQL

Job Description

Atyeti is looking for a lead 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. This is a pivotal leadership roll requiring you to provide on-the-ground leadership to your team, solutions to our stakeholders, and ensure the growth and stability of your team.

What You’ll Do:

• Work with your team to produce excellent solutions using best practices and SOTA tools and infrastructure
• Mentor Associate and Junior level data professionals and support their advancement
• Play a key role in migration to a best-practices cloud infrastructure
• 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
• Share in leadership of our company-wide data science group and help drive cross-engagement initiatives
• 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

What You Have:

• Strong python programming experience at a developer level
• 5-10 years total experience with 3+ years experience leading a data science team to include: data engineering, data analysis, machine learning and data visualization
• Excellent skills communicating complex technical 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
• Strong background in statistics and ML concepts, including proper support for accuracy evaluation, proper testing procedure and ground truth establishment, distribution testing
• Knowledge of various data set types including document, relational, graph, and timeseries
• Expert level SQL and Regex
• Large scale data experience
• Pytorch, Pyspark at scale, distributed OLAP databases (Redshift, Snowflake, etc), ML libraries such as sklearn

Bonus:

• Regulatory experience
• Experience with software development outside of python (.net, web programming)
• Data extraction experience (OCR, Web Scraping)
• Extensive deep learning architecture

Additional Information

Nice to Have:

• Good Interpersonal skills with experience of working with people spread across locations / time-zones
• Good written and oral communication skills.
• Experience of working in Investment Banking Technology
• Should be able to work independently and within team
• Ability to work effectively under pressure, challenging deadlines