Lucid Technologies Inc

This role is quantitative in nature and requires the individual highly capable of interrogating and analyzing massive account-level data using Snowflake SQL, Python. Skills for other programming, data mining tools such as SAS, R are preferred. He or she will join the data science team under consumer asset management of Ally auto finance business, with the responsibility to support collection strategy optimization and predictive analytics for consumer risk management. Daily work involves all phases of data science projects, including account-level data processing and validation, exploratory analysis for hypothesis testing and variable screening, communication and presentation to executive leadership team. This senior data scientist must be an innovative and strategic thinker, willing to challenge status quo, can learn quickly, is self-motivated and detail oriented.  

• Support complex business optimization projects via predictive analytics (e.g., customer segmentation, clustering) for Ally auto finance asset portfolio management; Independently prepare and analyze large, account-level consumer data from internal and external sources to identify customer behavior and strong risk indicators for Ally auto finance consumer

• Support the implementation of Ally collection treatment optimization solution (what delinquent customers should receive which collection treatments by when)

• Ability to think strategically, use sound judgement, and balance short and long-term risk decisions; Strong communication and collaboration skills; ability to work effectively across multiple team

• Understanding of risk management concepts and key performance drivers within consumer lending portfolios; Perform ad-hoc analysis, prepare crisp summary, and deliver recommendation

• Managing projects of various size/complexity and day-to-day tasks independently in fast paced environment; Mentor junior members in the team

• 3-5 years financial risk analytics, data science and/or predictive modeling work experience

• Bachelor’s Degree Preferred in Quantitative/Technical Discipline (Mathematics, Computer Science, Data Science/Analytics, Economics)

• Minimum 3 years of hands-on experience working with large, consumer account-level datasets using SQL (ideally Snowflake) and Python programming

• Good knowledge of statistics and data mining (e.g., Correlation, Regression, Decision Tree segmentation), and programming skills with exploratory data analysis using Python. Knowledge of R or SAS are preferred.

• Solid written and verbal communication skills, including the ability to effectively present data analytics results to internal and external stakeholders

• Highly self-motivated, with the ability to work effectively in fast paced environment

• Experience in loan-level predictive data mining for consumer finance industry

• Experience with supervised and unsupervised machine learning techniques using Python or other statistical programming packages such as R, SAS, MATLAB 

• Master's degree in a quantitative field

SQL, Python   4-5 Years   data processing and analytics

Thanks & Regards,

Siva Krishna D

Sr. US IT Recruiter

Lucid Technologies Inc

E: siva.d@lucidtechinc.com

O: 214-385-4144 Ext: 218

F: 214-889-5857

W: www.LucidTechINC.com