Data Scientist

  • Charlotte, NC
  • Posted 25 days ago | Updated 5 hours ago

Overview

On Site
Depends on Experience
Contract - W2
Contract - Independent
Contract - 12 Month(s)
No Travel Required

Skills

Responsibilities: * Work with stakeholders
identifying opportunities for leveraging data to solve for business challenges. * Identify valuable data sources / data sets that can be leveraged to improve results. * Analyze data to interpret against business opportunity and discover trends and patterns. * Process
cleanse
and verify the integrity of structured / unstructured data used for analysis. * Research and implement custom statistical models and machine learning algorithms. * Execute analytical experiments methodically to evolve an idea into successful solution. * Coordinate with engineering and software development team to integrate model into continuous business / process / software cycle. * Present information using data visualization techniques. * Communicate results and ideas to key stakeholders / decision makers. Qualifications: * Masters Degree in Computer Science
Statistics
Applied Math or relevant field * 7+ years' practical experience as a Data Scientist with proven track record * Strong math skills (e.g. statistics
algebra
multi-variable calculus) * Expertise with R
SQL and Python; familiarity with Scala
Java or C++ is an asset * Extensive background in data mining and statistical analysis * Deep understanding of real-life applicability and limitations of machine-learning algorithms * Problem-solving aptitude * Analytical mind and business acumen * Excellent communication and presentation skills Skills and Experience: * Experience with B2B
Financial Industry
Asset Management
Sales & Marketing is highly desired * Knowledge of a variety of machine learning techniques (clustering
decision tree learning
artificial neural networks
etc.) and their real-world advantages/drawbacks. * Knowledge of advanced statistical techniques and concepts (regression
properties of distributions
statistical tests and proper usage
etc.) and experience with applications. * Knowledge and experience in statistical and data mining techniques: GLM/Regression
Random Forest
Boosting
Trees
text mining
social network analysis
etc. * Expertise querying Relational / No-SQL databases and using statistical programming languages like R
Python
etc.
Data Scientist

Job Details

Responsibilities:
* Work with stakeholders, identifying opportunities for leveraging data to solve for business challenges.
* Identify valuable data sources / data sets that can be leveraged to improve results.
* Analyze data to interpret against business opportunity and discover trends and patterns.
* Process, cleanse, and verify the integrity of structured / unstructured data used for analysis.
* Research and implement custom statistical models and machine learning algorithms.
* Execute analytical experiments methodically to evolve an idea into successful solution.
* Coordinate with engineering and software development team to integrate model into continuous business / process / software cycle.
* Present information using data visualization techniques.
* Communicate results and ideas to key stakeholders / decision makers.

Qualifications:
* Masters Degree in Computer Science, Statistics, Applied Math or relevant field
* 7+ years' practical experience as a Data Scientist with proven track record
* Strong math skills (e.g. statistics, algebra, multi-variable calculus)
* Expertise with R, SQL and Python; familiarity with Scala, Java or C++ is an asset
* Extensive background in data mining and statistical analysis
* Deep understanding of real-life applicability and limitations of machine-learning algorithms
* Problem-solving aptitude
* Analytical mind and business acumen
* Excellent communication and presentation skills

Skills and Experience:
* Experience with B2B, Financial Industry, Asset Management, Sales & Marketing is highly desired
* Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
* Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
* Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
* Expertise querying Relational / No-SQL databases and using statistical programming languages like R, Python, etc.