Senior Data Scientist
Role details
Job location
Tech stack
Job description
The Intelligence Unit of the Business Operations team seeks a Data Scientist with strong analytical and communication skills to join our team. We develop algorithms that involve learning from core systems, such as HCM, ERP, ATS, CRM, internal products, and Staffing Systems, in order to generate and improve existing data models. Your Day-to-Day
On a typical day, you will work closely with talented data analysts, data engineers, software engineers, and business groups. As a successful data scientist in our team, you are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems, through collaboration with engineering and business teams. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.
Major responsibilities include:
-Analyzing and translating business needs into long-term solution data models, utilizing code for analyzing data, and building statistical and machine learning models and algorithms.
-Evaluating implemented data systems for variances, discrepancies, and efficiency.
-Supporting decision-making by providing requirements to develop analytic capabilities, platforms, pipelines, and metrics then using them to analyze trends and find root causes of model inaccuracy. Are You a Fit?
Requirements
Background in any of these areas:
- Statistics and Applied Math, Computer Science, Finance, and Economics.
- Python/R/Scala and SQL, demonstrating best practices for data coding to ensure consistency.
- English Proficiency
- 5+ years of experience working in the Data Science field
- Data-focused applied mathematics (statistical analysis)
Preferred Qualifications:
- Data analysis tools and libraries such as Python (NumPy / SciPy / scikit-learn / pandas / matplotlib), R, SAS, SPSS, etc
- Database Experience: Ability to perform CRUD operations on relational and non-relational datasets.
- Big Data Technologies Experience: Ability to create ETL pipelines and use machine learning algorithms.
- Data Visualization: Display data to provide insights: show patterns, trends, or correlations in a single plot. The ability to produce dynamic and interactive data visualizations is a plus.