Key Responsibilities:

Create innovative, sophisticated analytic models to address critical issues but also meet key business criteria (cost/risk/business impact) and key technical criteria (reliability/validity/predictability).
Apply machine learning techniques and statistical methods to automatically identify trends, patterns and frictions in the employee experience.
Interview stakeholders to incorporate business requirements and inputs from research, science, product, and engineering partners and translate them into concrete requirements for data science projects.
Define and conduct experiments and communicate insights and recommendations to product, engineering, and business teams.
Work with data engineers and software development engineers to deploy models and experiments to production.
A clear passion for making a positive impact on employees' lives through your work.
Identify and advocate for technical options related to machine learning, data mining, and other statistical approaches.
Identify and recommend opportunities to automate systems, tools, and processes.
Ability to work in a highly collaborative environment with peers that have a range of technical aptitudes.

Basic Qualification:

Bachelor's Degree in a quantitative field (such as Computer Science, Economics, Mathematics, Statistics, Engineering, Operations Research, Machine Learning, or related field).
2+ years’ experience working as a Data Scientist.
3+ years’ experience programming in Java, C++, or other programming language, as well as experience using common data scientist software development and statistical analysis tools (e.g., Python, R, Scikit-learn).
Experience writing and optimizing SQL queries in a business environment with large-scale, complex datasets.
Experience applying various machine learning techniques and a deep understanding of the key parameters that affect their performance.
Highly proficient at statistical analysis, model development, model validation, and model implementation for large-scale applications.

Preferred Qualification:

MS or PhD in a quantitative field (such as Computer Science, Economics, Mathematics, Statistics, Engineering, Operations Research, Machine Learning, or related field).
4+ years industry experience working as a Data Scientist with experience in predictive modelling, data analysis, and a track record of building Machine Learning and/or Deep Learning models.
4+ years of experience with experiment design involving algorithm development, machine learning, data mining, and use of other statistical approaches.
Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relation.
Experience with machine learning software systems, big data software systems, data mining, and modern methods for parallelized processing of large, distributed datasets (e.g., Spark, Hadoop, Map-reduce).
History of putting ML models into production.
Experience using an object-oriented language to write production-ready code.
Experience using AWS products (Redshift, Sagemaker, Athena, S3, EC2, QuickSight) and with development on the AWS platform.
Knowledge of professional software development life cycle, including coding standards, code reviews, source control management, build processes, testing and operations.
Excellent ability to convey complex mathematical and scientific concepts to business stakeholders.

Data Scientist