Job Location: Maryland Heights, MO
Spectrum’s Product and Technology team creates, develops, and operates the nation’s fastest mobile service, most reliable internet service, most viewed live TV app, and the most advanced WiFi, serving nearly 100 million users and 500 million devices. We are transforming the next era of connectivity and entertainment experiences together.
This position is eligible to work in a hybrid work model (combination of in-office and remote days)
JOB SUMMARY
Responsible for driving 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.
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.
Ensure analytics products are flexible, modular, and contain reusable code base.
Coordinate technical activities across projects and the organization.
Interact with various stakeholders to understand their business needs, communicate project status and develop relationships to ensure satisfaction. Utilize experience to anticipate hurdles & recommend solutions in line with business needs.
Provide technical oversight and expertise for activities including experimental design, machine learning, ad-hoc analytics, and statistics.
Increase speed to delivery by architecting and implementing automated solutions across the data and analytics lifecycle.
Lead large-scale exploratory data analyses for new data sources or new uses for existing data sources. Establish links across existing data sources and find new, interesting data correlations.
Research and develop machine learning models and algorithms for data analysis and discovery.
Assist in making strategic recommendations and implementations for data architectures, data collection processes, and analytics platform integration.
Responsible for interpretation of results – for both causal inferences and predictive sensitivity and specificity.
Synthesize appropriate recommendations for action and changes.
Teach techniques and explain tools used to a broad set of business-intelligence, data, and analytics professionals with varied backgrounds.
Exercise thought leadership and discretion in tailoring the tools, approaches, and data used to meet the needs of the particular problem. Lead teams to select, implement, and integrate new technologies into the team’s work process.
Deliver results using metrics-driven analysis, and communicating the costs and tradeoffs of ideas to stakeholders and top management.
Direct and integrate the work of others to produce high quality work products.
Mentor and train junior team members and set strategic vision for assigned projects.
REQUIRED QUALIFICATIONS
Required Skills/Abilities and Knowledge
Ability to read, write, speak and understand English
- Expert-level skills and experience with a statistical scripting language such as R, Python, Matlab, etc. in support of advanced analytics
- Advanced-level skills with databases, including SQL and utilizing data stored in complex schemas
- Expert-level logical and analytic skills
- Broad experience and solid theoretical foundation on the modeling process using a variety of algorithms
- Expert understanding of modern machine learning technology and tools in order to produce model scoring code
- Data profiling, distributions, confidence intervals, hypothesis testing
- Holdout for testing, cross-validation
- Data pre-processing, exploratory data analysis using a variety of techniques
- Regression and classification using techniques such as linear models, GLMs, and tree-based methods
- Interpretation of model results, consideration of causality, treatment of multicollinearity
- Expert synthesis and presentation skills
- Ability to communicate results and recommendations to a wide variety of audiences including executive leadership
- Expert 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 Teradata: SQL, UDFs, interpreting explain plans, basic performance-tuning, and use of database catalog
- Knowledge of other relevant tools such as SAS, SPSS, Alteryx, Linux
- Knowledge of other relevant techniques such as text analysis and text mining
- Familiarity with the open-source ecosystems surrounding R (CRAN), Python (PyPi), and/or Hadoop
- Extracting data and delivering complete analytics and machine learning products primarily using Python; secondary experience with R, Java, JavaScript, C, C++, Scala, or Julia is an asset
- Experience with other database and data store technologies, such as NoSQL, key-value, columnar, graph, and document
- Visualization or BI tools, such as Tableau, Looker, Microstrategy, RapidMiner, or anything Microsoft Power BI
- Creating proof of concept experiments for analytics, machine learning, or visualization tools that includes hypothesis, test plans, and outcome analysis
- Experience in receiving, converting, and cleansing big data
- Expert statistical knowledge and techniques
- Program, product, or project management experience delivering analytics results
- Comprehensive background in Linux/Unix/CentOS and Windows installation and administration
- Ability to identify and resolve end-to-end performance, network, server, cloud, and platform issues
- Expert pattern recognition and predictive modeling skills
- Experience with Hadoop, Spark, and/or Snowflake
- Keen 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 – 10
SQL/R/SAS Programming – 10
Lead the design, develop and deployment machine learning and analytics models – 5+
PREFERRED QUALIFICATIONS
Preferred Skills/Abilities and Knowledge
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
WORKING CONDITIONS
Office environment
Charter Technical Engineering Center
Highly collaborative and innovative work space
Occasional Travel BDA710 320839 320839BR
Submit CV To All Data Science Job Consultants Across United States For Free
Leave a Reply