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Senior Data Scientist
  • Python
  • Spark
  • SQL
  • SAS
  • Linux
  • Data Analysis
  • Database
  • Modeling
  • Hadoop
  • SPSS
  • Business Analysis
Spectrum
Greenwood Village, CO 80121
152 days ago

JOB SUMMARY
The Sr Data Scientist job is responsible for executing the full-scope of advanced analytic techniques with the objectives of creating causal inferences, predictions, and recommendations for improvements to business processes, and the metrics to monitor those improvements. This position requires a strong command of techniques and algorithms as well as a demonstrated practical ability to determine where to invest time, synthesize actionable findings across diverse assignments, and present these findings to an audience with varying levels of background in analytics.

MAJOR DUTIES AND RESPONSIBILITIES
Plan and lead the execution of the analytics life-cycle, leveraging significant experience in leading this type of work in previous roles

Survey varied data sources in relational databases, Hadoop, flat files, and external sources for analytic relevance

Execute the full-scope of advanced analytic techniques

Perform problem formulation, requirements analysis, and planning

Responsible for data surveying, profiling, and pre-processing

Model data management for validation (e.g. holdout, cross-validation)

Select algorithm and execution

Responsible for interpretation of results – for both causal inferences and predictive effectiveness

Synthesize appropriate recommendations for action and changes

Present findings, suggested actions and changes to a broad audience, and manage follow-ups and execution

Help teach and explain techniques and 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

Perform other duties as required

REQUIRED QUALIFICATIONS
Skills/Abilities and Knowledge
Ability to read, write, speak and understand English
Expert-level skills and experience with R (required) and/or Python (desired) (including relevant packages) in support of advanced analytics
Advanced-level skills with relational 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
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 linear models, GLMs, and tree-based methods
Interpretation of model results, consideration of causality, treatment of multicollinearity
Strong synthesis and presentation skills
Ability to communicate results and recommendations to a wide variety of audiences
Basic understanding of data architecture, data warehouse and data marts
Experience in the telecommunications industry, or two other consumer-based industries
Demonstrated ability and desire to continually expand skill set, and learn from and teach others

PREFERRED QUALIFICATIONS
Skills/Abilities and Knowledge
Experience with Teradata: SQL, UDFs, interpreting explain plans, basic performance-tuning, and use of database catalog
Operations-research background, in particular focused on large labor operations such as field ops, technical support, and sales
Background with Cable systems and operations
Experience with Hadoop, particularly HIVE and Spark
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

Education
Master's degree in computer science, mathematics, statistics, operations research or other quantitatively-focus field

Related Work Experience
10+ years of Statistical Analysis
8+ years of Business Analysis
8+ years of SQL/R/SAS Programming
2+ years of Database Design or Database Modeling

WORKING CONDITIONS
Office environment
Travel as required

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