Data Scientist

Rapinno Tech; Englewood (CO); On-site; USD 80,000 - 120,000; Full time

Job summary

A technology firm in Englewood, Colorado is seeking a skilled Data Scientist for their Wi-Fi CPE Development team. The ideal candidate has a Master's in Computer Science or Electrical Engineering and is proficient in Python, SQL, and data science techniques. Responsibilities include analyzing large datasets, developing machine learning models, and creating tools for data analysis. The role requires strong communication skills and the willingness to work in an office environment. Knowledge in Wi-Fi technologies is a plus.

Qualifications

• Proficiency in Linux and scripting.
• Experience using data science and visualization tools.
• Fundamental algorithmic and data structure knowledge.

Responsibilities

• Employ data science techniques and analyze large datasets.
• Identify root causes of RF and wireless issues.
• Develop models and software tools for large wireless metrics.

Skills

Data science techniques

Machine learning

Data cleaning

Python

SQL

Verbal and written communication

Education

Master's degree in Computer Science or Electrical Engineering

Tools

Python libraries (e.g., Pandas, matplotlib)

Machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)

Job description

Note: Need Only US Citizen, Green Card, EAD-GC, J2 EAD, H4 EAD, L2 EAD, and TN Visa.

Job Title: Data Scientist

Location: Englewood, CO

Duration: 06+ Months Contract

Must Skill Set

Wi-Fi CPE Development

Job Description

We are seeking a Data Scientist to join our Wi‑Fi CPE Development team in Englewood, Colorado. We define, develop, and test the hardware and software on Spectrum Advanced In‑Home Wi‑Fi routers deployed to millions of customer homes across the United States. Ideally, we are looking for a skilled data scientist with a good understanding of data models, machine learning models, data cleaning, and some domain knowledge in the field of Wi‑Fi and/or wireless performance metrics.

Responsibilities

• Employing data science techniques and analyzing large datasets to assist in proactive network management of larger wireless networks
• Identify root causes of RF and wireless issues encountered with equipment deployed in the lab, at test houses, or in production networks
• Understand and analyzing test results
• Developing models and software tools to organize and analyze large collections of wireless metrics
• Developing software and tools for interacting with cloud services, databases, and large datasets
• Creating visualizations and communicating insights across teams
• Collecting data from various sources (cloud data warehouse, internal database, third‑party APIs)
• Developing and implementing supervised/unsupervised/reinforcement machine learning algorithms

Must have:

• Master’s degree in Computer Science or Electrical Engineering
• Proficiency in Linux and scripting
• Proficiency in Python and Jupyter notebooks
• Proficiency in SQL and relational/non‑relational database
• Experience using data science and visualization tools, e.g. Pandas, matplotlib, etc.
• Experience with machine learning tools/libraries, especially in Python, e.g. scikit‑learn, TensorFlow, PyTorch, etc.
• Fundamental algorithmic and data structure knowledge
• Strong verbal and written communications skills
• Willingness to work in an office environment
• Ability to work with colleagues across teams

Desirable to have:

• Ph.D in Computer Science or Electrical Engineering or 3+ years of experience in software development in ML or data science fields
• Experience creating and maintaining live dashboards
• Experience with neural networks and deep learning algorithms
• Experience with MLOps - automate ML pipelines, monitor model performance, version control of data/model/code, scale models using Kubernetes and containers
• Experience architecting and deploying cloud services, databases, and controllers
• Familiarity with cloud environments such as AWS
• Knowledge of Wi‑Fi technologies and protocols (i.e. IEEE 802.11a/b/g/n/ac/ax)
• Experience with managed Wi‑Fi systems and equipment, including Wi‑Fi controllers