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About Us:

Position Purpose:

The Data Scientist role plays an integral role in decision-making at Stericycle Compliance Solutions. This individual is responsible for providing strategic recommendations grounded in data analysis and statistical models. A commitment to continuous improvement is critical as it will ensure the continued success of our data analytics initiatives which drive increased revenue, cost reduction, and customer retention.

Key Job Activities:

Reporting/Analysis – Develop and publish reporting and analytics as a result of tested hypotheses and provide user-friendly outputs for various departments (e.g., Sales, Marketing, and Executive leadership). Design reporting to provide insight into customer segments, campaign effectiveness, business initiatives, and the relationships.

Predictive analytics - Test business hypotheses across various departments to construct predictive models. Work in cross functional team to identify new hypotheses. Test sensitivity/impact of current and proposed business initiatives on various customer segments.

Data Model Management – Set up experimental designs to answer business questions and opportunities. Continuously measure model effectiveness and performance against business KPIs. Regularly conduct data validations to ensure models remain relevant.

Business Management – Participate in various business improvement activities and deep-dive initiatives adding insight where predictive analytics are required to forecast impact/results. Develop partnership with Information Systems to gain insight into upcoming data changes or new data availability.

Data Quality - Execute different data analytics to ensure the completeness, quality, and consistency of data used for analytics across systems. Works across departments to understand inputs and ensure reliability while providing feedback/recommendations to improve quality.

Performs other related duties as required or requested.

Education:

Bachelor's Degree in a quantitative field such as statistics, mathematics, information systems, computer science, or economics. Master’s or PhD Degree in an analytics related field such as statis-tics is a plus.

Experience (EMEAA):

Have strong statistical, mathematical, predictive modeling, or machine learning skills.

Two to four years of experience in working with large datasets, and relational databases (SQL).

Experiencing using Tableau, SAP, TM1, and Business Objects would be an asset

Experience using Microsoft Office applications, in particular, PowerPoint and Excel, is a requirement.

Ability to articulate and present complex data in a user-friendly format is critical to the success of this role.

Must have the ability to work collaboratively in a team environment.

Must be subject matter expert with a passion for digging into any dataset by researching the relevant information on the subject to use the data effectively.

Comfortable and proficient in managing projects, including the use of Business Analyst skills.

Proficiency in Python (Pandas, NumPy) is a requirement, including strong data cleaning and manipulation skills.

Data visualisation using Python (Matplotlib/seaborn/plotly/bokeh), Tableau, and Excel.

Building production level machine learning models using Python (scikit-learn, TensorFlow/keras, flask).

Cloud computing (AWS, Google Cloud, Azure).

Certifications and/or Licenses:

Benefits:

Disclaimer:

The above description is meant to provide a summary of the nature and level of work being performed; it should not be construed as an exhaustive list of all responsibilities, duties and requirements of the job. This document does not create an employment contract, implied or otherwise. Stericycle will consider requests for workplace accommodations for protected physical or mental limitations in accordance with its human resources policies and local laws. To the extent permissible under local law, and consistent with business necessity, Stericycle reserves the right to modify the content formally or informally, either verbally or in writing, at any time with or without advance notice.