Company
Cox Communications, Inc.Job Family Group
Job Profile
Management Level
Flexible Work Option
Travel %
Work Shift
Compensation
Compensation includes a base salary of $99,000.00 - $165,000.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate’s knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.Job Description
Cox Communications is seeking a Senior Data Scientist for Network Analytics Reliability Enablement Team (NARE). This role will report to a Manager of Data Science and will be responsible for architecture and development of analytics applications for the Service Health platform. As a Data Science application developer, you act as a cross breed between a data scientist, data engineer, and an application developer; delivering scalable infrastructure which can both run new data science models, and facilitate the onboarding of additional models across the organization. This role will play a central part in the ongoing design and build of data models, core platform infrastructure, data integration layers, graph database algorithms, and AWS development. It’s an exciting opportunity for someone who is a proven advanced analytics developer who knows their way around analytics algorithms, tools, and technologies.
What You’ll Do:
Lead initiatives to tackle the most challenging problems within Cox’s analytical portfolio.
Develop analytics applications, applying best practices for design, development, and testing. Recommend tools, services, and processes as needed.
Use expertise in machine learning, data mining, prompt engineering, and information retrieval to design and build next-generation analytics engines and services.
Architect scalable and maintainable solutions within the AWS ecosystem.
Collaborate with N.A.R.E leadership and engagement teams to present reusable solutions and insights to the business.
Review existing services for scalability, maintainability, and opportunities to reduce complexity.
Assist in tracking and maintaining project goals and roadmaps.
Design complex models and algorithms that drive innovation across the organization.
Mentor junior team members and provide constructive feedback on specific projects.
Who You Are:
Minimum Qualifications:
Bachelor’s degree in a related field with 4+ years of experience, or an equivalent combination of education and experience (e.g., Master’s degree and 2 years of experience, Ph.D. and up to 1 year of experience, or 16 years of experience in a related field).
4+ years of experience with Python.
2+ years of experience with cloud technologies in software engineering or data science.
1+ year of experience working with big data systems (e.g., Hive, Athena, Big Query).
Strong programming skills with proficiency in tools like SQL, Python (pandas, numpy, scipy, scikit-learn), PySpark, Tableau, etc.
Experience with AWS services such as Lambda, Step Functions, and Athena.
Excellent data visualization skills and the ability to craft compelling stories with data (Tableau preferred).
Familiarity with source code version control software (e.g., Git, Bitbucket) and CI/CD pipelines (e.g., Jenkins).
Innovative mindset and willingness to embrace new approaches.
Strong communication and presentation skills, with the ability to explain complex analytics findings to non-technical stakeholders.
Strong business acumen and the ability to communicate insights clearly to drive strategic decisions.
Preferred Qualifications:
Experience with additional AWS services such as S3, Glue, CloudWatch, EventBridge, EC2, EMR, RedShift, SQS, RDS, IAM, and Terraform.
Practical experience building real-time applications in AWS (e.g., OpenSearch).
Experience with in-memory storage solutions like DynamoDB or Redis.
Experience with AWS Gen AI models (Claude, Llama) and prompt engineering.
Experience in ETL pipeline development.
Experience within the telecommunications or cable industry, or consulting.
Experience in automated test design and implementation.
Knowledge of data store selection for large-scale applications with high data volume and/or high read/write demands.
Familiarity with Agile methodologies, particularly Scrum or as a Product Owner.
Practical experience applying advanced machine learning, data processing, and AI techniques to reduce mass transactions and optimize customer experience.
Benefits
About Us
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