Data Scientist

Cogeco•Quincy, MA

2d•Onsite

About The Position

Cogeco is seeking a skilled and motivated Data Scientist to join its Data Science and Analytics practice. This role is crucial in developing and implementing data models and strategies to enhance customer acquisition, retention, and overall business performance. The Data Scientist will collaborate with cross-functional teams to identify opportunities, develop advanced analytics, and deploy machine learning models that directly impact commercial growth and customer experience. The role involves applying expertise in artificial intelligence through machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. Collaboration with business partners is key to defining technical problem statements and hypotheses, developing efficient and accurate analytical models, and integrating them into analytical data products or tools with the support of a cross-functional team.

Requirements

Bachelor’s degree required.
Graduate degree in quantitative discipline and demonstrated Data Science skill set, plus 2 years work experience.
Proficiency writing complex SQL queries.
Advanced hands-on experience with the Python data science stack.
Owning the full Data Science life cycle from ideation to production.
Strong understanding of quantitative approaches, their benefits, and their limitations.
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 datasets.
Agile/Digital Experience: Openness to working in Agile environments with multiple stakeholders.
Exceptional communication and collaboration skills to understand business partner needs and deliver solutions.

Nice To Haves

Experience with data visualization tools preferred — Tableau, PowerBI, Looker, Plotly, etc.

Responsibilities

Develop predictive modeling and machine learning solutions to complex business problems, creating value for the business.
Transform data into insights that help to improve the value of the business.
Execute exploratory data analysis, data preprocessing, model development, model deployment, and monitoring.
Utilize machine learning techniques to improve customer segmentation, churn prediction, and personalized marketing efforts.
Plan and execute analytical experiments to help solve business problems.
Propose solutions and strategies to business challenges.
Continuously refine and improve models based on feedback and changing business needs.
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.
Collaborate with business partners to develop novel ways to meet objectives utilizing cutting-edge techniques and tools.
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.
Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts, and developers.
Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytic data products.
Engineer features by using business acumen to find new ways to combine disparate internal and external data sources.
Build and deploy agentic AI solutions that leverage autonomous reasoning and tool-calling to automate end-to-end workflows and improve decision-making efficiency.
Share passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods, and standards.
Collaborate, coach, and learn with a growing team of experienced Data Scientists.