Lead Data Scientist

3 weeks ago

Burlington, Canada Cogeco Connexion Inc Full time

Our culture lifts you up—there is no ego in the way. Our common purpose? We all want to win for our customers. We aim to always be evolving, dynamic, and ambitious. We believe in the power of genuine connections. Each employee is a part of what makes us unique on the market: agile and dedicated.

Time Type:
Regular

Job Description:
Lead Data Scientist

About The Job

Position Summary:
As the Lead Data Scientist within the Data Science and Analytics team at Cogeco, you will be at the forefront of our digital transformation efforts. Working closely with the Director of Data Science and Analytics, your primary focus will be to lead a team of data scientists and execute on high-impact advanced analytics projects.

Your responsibilities will extend beyond individual projects to encompass leadership of the practice, acting as a mentor to fellow Data Scientists and Analysts within the DS&A team. Success in this role will require a well-executed balance between leading high-visibility projects and advancing the professional growth of your team members.

In this role, you will play a key part in developing and implementing data models and strategies to improve customer acquisition, retention, and overall business performance. You will work closely with cross-functional teams to identify opportunities, develop advanced analytics, and deploy machine learning models that directly impact commercial growth and the customer experience.

Responsibilities:

- As a Lead Data Scientist at Cogeco, you will develop predictive modeling and machine learning solutions to complex business problems creating value for the business.
- This individual will have both a hands-on and strategic role in data science efforts and will also help to mentor a team of data scientists accelerating advanced analytics and artificial intelligence at Cogeco.
- Your work will transform data into insights for internal stakeholders including Marketing, Sales, Product, Network, and others.
- Utilize machine learning techniques to improve customer segmentation, churn prediction, and personalized marketing efforts.
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
- Plan and execute analytical experiments to help solve business problems.
- Leverage advanced analytics techniques to develop deep knowledge of the customer experience, use data and analytics to optimize marketing campaigns, and develop strategies through insights to attract new customers and retain existing ones.
- Effectively communicate the analytics approach and data science lifecycle with leadership and business partners.
- Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems
- Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.

Qualifications:

- Bachelor’s degree required, MS or PhD preferred.
- Bachelor’s in Data Science, Computer Science, Engineering, Statistics and 10+ years experience required OR Graduate degree in quantitative discipline and demonstrated Data Science skill set, plus 5+ years work experience.
- A strong Python and SQL programmer with demonstrated proficiency in data extraction, data engineering, data analysis, machine learning, data modeling and pipeline automation.
- Track record of analytical projects covering all stages of the data science lifecycle.
- Strong understanding of quantitative approaches, their benefits, and their limitations.
- Experience deploying analytical and AI solutions, including generative AI, in a business setting with proven results
- Analytical ability required to gather data, perform transformation, perform complex analysis, solve both business and technical problems.
- Proficiency with data mining, mathematics, and statistical analysis.
- Experience in pattern recognition and predictive modeling.
- Experience with cloud platforms like Google Cloud, AWS, or Azure.
- Excellent interpersonal, communication, listening, and presentation skills.
- Excellent problem-solving skills and the ability to work independently as well as in a team.
- Must have proficiency with Machine Learning to solve clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets.
- Experience with data visualization tools preferred — Tableau, PowerBI, Looker, R Shiny, Plotly, etc.

Agile/Digital Experience:

- Strong understanding of Agile methodologies.
- Openness to working in Agile environments with multiple stakeholders.
- Exceptional communication and collaboration skills to understand business partner needs and deliver solutions.

About You:

- Bias for action, with ability to deliver outstanding results through task prioritization and time management.
- Demonstrated ability to efficiently learn and solve new business domains and problems.
- Number

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