JOB SUMMARY As part of this group, the Data Scientist job is responsible for executing the full-scope of advanced analytic techniques with the objectives of improving business processes, enhancing product personalization, and improving customer retention through discovery of causal relationships, predictive analysis, and recommender systems. Additionally, role will also be responsible for developing experiments and metrics to test and monitor system improvements. 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 Plan, lead, and execute the complete analytics life-cycle for problem solving, including:
- Requirements gathering
- Problem formulation
- Data grooming
- Data exploration
- Model prototyping
- Model validation
- Algorithm productionalization
Survey varied data sources for analytic relevance, including:
- Stream source
- Distributed file systems
- Relational databases
- Flat files
- External sources
Interpret, synthesize and communicate results of analyses to effect action and changes within the organization Collaborate across teams to integrate analytic products with existing production architectures, develop execute and evaluate courses of action, and socialize results 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 QUALIFICATIONSSkills/Abilities and Knowledge
- Ability to read, write, speak and understand English
- Strong communication and presentation skills
- Expert-level skills and experience with Python (preferred), R, Matlab, or other analytics languages
- Experience with relational and NoSQL databases
- Expert-level quantitative analysis skills including interpretation of model results, consideration of causality, treatment of multicollinearity
- Broad experience and solid theoretical foundation on the modeling process using a variety of algorithmic techniques, including Machine Learning, NLP, and Graph/Network Analytics
- Data pre-processing, exploratory data analysis using a variety of techniques
- Basic understanding of data architecture, data warehouse and data marts
- Experience in the telecommunications industry, or other consumer-based industries
- Demonstrated ability and desire to continually expand skill set, and learn from and teach others
PREFERRED QUALIFICATIONSSkills/Abilities and Knowledge
- Experience with BigData tools, particularly HIVE, Spark, Spark Streaming, and GraphX
- Experience with Linux based operating systems
- Experience with advanced analytics libraries in python such as numpy, sci-kit learn, and pandas
- 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
Education Advanced degree in computer science, mathematics, statistics, physics, operations research or other quantitatively-focus fields Related Experience Years Work Experience Phd 3+ Masters 6+ Bachelors 8+ Required Skills : - Professional experience with Machine Learning - Education in STEM, applied mathematics, or statistics o Background in math and programming essentially - Strong SQL and ETL experience - Python, Java, or R o Scala is nice to have - Modeling experience: statistical, predictive, regression, ML, etc. o Binary classification models, continuous target models, etc. - Experience with Big Data tools and/or working with large data sets - Any cloud experience (ideally AWS)- in the process of moving everything over to AWS - Open and willing to do whatever is needed as the needs of the projects will change Will need to do live coding with Python or SQL during the interview
Basic Qualification : Additional Skills : Long term Background Check :Yes Notes : Selling points for candidate :Long term Project Verification Info : Candidate must be your W2 Employee :Yes Exclusive to Apex :No Face to face interview required :Yes Candidate must be local :Yes Candidate must be authorized to work without sponsorship ::No Interview times set : :No Type of project :Assessment/Analysis Master Job Title :Data Scientist Branch Code :Denver