Spectrum

Principal Data Scientist I

Spectrum, Stamford, CT, United States

JOB SUMMARY

Responsible for leading the development of data-driven solutions to Charter’s business problems. Utilizes analytical, statistical, and programming skills to clean, aggregate, and analyze large data sets and interpret results. This position requires a strong command of statistical techniques and machine learning algorithms, as well as a demonstrated practical ability to determine where to invest time, synthesize actionable findings across diverse assignments, and present findings to audiences with diverse agendas and varying levels of technical expertise. This role will be responsible for the delivery of insights and analytics on the trends and causes of quality-of-service and service-rate fluctuations in our Internet and Video products. Promptly identifying problematic network equipment, configuration, maintenance, and other controllable drivers while separating out the non-controllable elements such as usage and weather, resulting in insights delivered to internal stakeholders to resolve identified issues. Will require a range of applied analytic techniques, from simple crosstabs to state-of-the-art AI/ML algorithms to measure the causal impact of drivers. In particular, we are expanding our approaches and techniques to include the fast-developing field of Causal AI. These techniques will be applied against a set of large and growing data – over 30 million rows of 100 columns per day, and growing. Compute resources will include high-end relational data warehouse and cloud-based GPU-heavy compute for AI/ML. This role will be considered an intellectual co-owner of the algorithms and procedures methods used to derive causal insights from observational data. Works with R&D and development (analytic requirements) against backlog of desired features. One will perform R&D on and apply these techniques to real-world problems in order to further refine and develop the methods and implementation of them. In addition, this role will be the lead applied analyst on the team, responsible for reviewing work product, providing constructive and coaching feedback to junior team members, and delivering key results to senior stakeholders in a clear, polished, and professional manner.

MAJOR DUTIES AND RESPONSIBILITIES

Actively and consistently support all efforts to simplify and enhance the customer experience
Plan and lead the complete analytics life-cycle for problem solving, including: requirements gathering, problem formulation, data grooming, data exploration, model prototyping, model validation, and algorithm productionalization
Leverage consultative experience delivering insights on large structured data to senior operational executives with strong communications skills (verbal, written powerpoint)
Perform mid-level and advanced analytics using a range of techniques from basic (pivot table) to advanced (Causal AI tools and models)
Troubleshoot, debug, solve problems where the analytic approach, model, or tool is not performing as well as needed, and lead the exploration of vendors in the marketplace that can meet this need, enabling buy versus build
Participate in reviewing vendor tools and products that might be fit for our needs; consistently keep up-to-date in the latest market and academic developments in Causal AI
Plan effectively to ensure analytics products are flexible, modular, and contain reusable code base
Identify future technical needs of assigned projects to continue to grow capabilities of organization
Coordinate technical activities across projects and the organization

WHAT YOU’LL BRING TO SPECTRUM

Required Qualifications

Required Skills/Abilities and Knowledge

Ability to read, write, speak and understand English
Advanced-level skills in one or more scripting, analysis, or ETL languages, ability to readily read and adapt others’ code, and ability to rapidly learn new languages or techniques
Expert-level skills and experience with analysis language such as R and/or Python (including relevant packages) in support of advanced analytics
Comprehensive experience and theoretical foundation of the properties of the major families of machine learning models (regression, decision trees, clustering, SVMs, neural networks)
Experience with modern machine learning technology and tools in order to produce model scoring code
Basic background (awareness) and strong interest in further developing expertise in Causal AI techniques, e.g., Paradoxes and blunders that result from lack of causal awareness, structural causal models, causal graphs, causal discovery, and causal inference. Ability to keep abreast of the latest developments in this field, via regular review of published work (books and papers) on these topics
Command of advanced mathematical concepts including calculus, PDEs, probability, and statistics, and the ability to independently learn any necessary additional concepts
Effective synthesis and presentation skills
Ability to communicate results and recommendations to a wide variety of audiences including executive leadership
Understanding of data architecture, data warehouse and data marts
Demonstrated ability and desire to continually expand skill set, and learn from and teach others
Experience with other database and data store technologies, such as NoSQL, key-value, columnar, graph, and document
Extensive experience with large data sets and the tools to obtain, transform, and store data on Big Data and streaming services
Program, product, or project management experience delivering analytics results
Comprehensive background in Linux/Unix/CentOS or Windows installation and administration
Ability to identify and resolve end-to-end performance, network, server, cloud, and platform issues
Pattern recognition and predictive modeling skills
Effective attention to detail with the ability to effectively prioritize and execute multiple tasks

Required Education
Bachelor's degree in computer science, statistics, operations research and/or equivalent combination of education and experience

Required Related Work Experience and Number of Years

Data manipulation and statistical modeling as a Scientist, Consultant, Architect, DBA, or Engineer - 8
SQL/R/SAS Programming - 8
Lead the design, develop and deployment machine learning and analytics models - 3+

PREFERRED QUALIFICATIONS
Preferred Skills/Abilities and Knowledge

Experience with Hadoop, HIVE, SPARK, and/or Snowflake
Strong basic analytics skills in SQL, Excel
Tableau and Python a plus
Reading, merging, and drawing from research papers, finding the right path forward, local R&D on techniques, and implementing in practice
Knowledge of other relevant tools such as SAS, SPSS, Alteryx, Linux
Knowledge of other relevant techniques such as text analysis and text mining
Operations-research background, in particular focused on large labor operations such as field ops, technical support, and sales
Background with cable and/or telecommunications

Preferred Education
Master’s degree in related field (ML / AI / DS)

WORKING CONDITIONS

Office environment
Charter Technical Engineering Center
Highly collaborative and innovative work space
Occasional Travel

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