Data Scientist

  • location: Jacksonville, FL
  • type: Temp to Perm
  • salary: $50 - $75 per hour
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job description

Data Scientist

job summary:
Our client's Information Technology organization is undergoing a significant transformation from an IT service provider to a strategic business partner and trusted driver for innovation. They are actively leveraging automation technology, large-scale data modeling, and advanced data analytics to enable operational excellence, customer experience improvement, and end-to-end supply chain optimization. If you want to work in a fast pace and non-bureaucratic environment, valuing learning and personal growth, collaborating with a team of high caliber and driven professionals, having the opportunity to work on leading edge business problems and innovations that can help change the company and the industry, then this is the right opportunity for you!

Your primary focus will be in applying data mining techniques, doing statistical analysis, designing and implementation practical optimization models, and building high quality prediction systems integrated with our operations. You will collaborate with the business intelligence and data warehouse teams as well as key business stakeholders across operations, commercial development, and supporting functions on identifying and defining business problems, designing and implementing advanced analytics models, testing on real data, and implementing in production environment. You will be responsible and involved with the entire life cycle of implementing machining and optimization solutions.

location: , 0
job type: Contract
salary: $50 - 75 per hour
work hours: 8am to 5pm
education: Bachelors
  • Work with business partners and IT teams to explore, design, implement, and support advanced analytics solutions that aims at optimizing operations, providing predictive insights, improving customer services and experience, and optimizing supply chains.
  • Working with IT teams closely to ensure all advanced analytics solutions, including statistical, machine learning, optimization solutions are fully integrated with IT Systems so users can leverage these analytics solutions in a seamless fashion.
  • Selecting features, building and optimizing classifiers using machine learning techniques.
  • Possesses the ability to define, extract, analyze, and implement insights within data tools.
  • Data mining using state-of-the-art methods.
  • Enhancing data collection procedures to include information that is relevant for building analytic systems.
  • Processing, cleansing, and verifying the integrity of data used for analysis.
  • Doing ad-hoc analysis and presenting results in a clear manner.
  • Creating automated anomaly detection systems and constant tracking of its performance.
  • Bachelor's degree in IT, Computer Science, Math, Physics, or related field.
  • Master's degree in Business Analytics, Machine Learning, Optimization or related field.
  • Minimum of five years of experience as a Data Scientist
  • Ability not only to build analytical models, but to analyze and understand real world, complex business data, and come up with pragmatic solutions that provide useful insights
  • Biased toward pragmatic insights that can drive real management actions instead of theoretical observations.
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Experience with one or more common data science toolkits, such as R, Weka, NumPy, Plotly, Azure Data Lake Analytics, MatLab, etc. Excellence in at least one of these is highly desirable.
  • Great communication skills that can both speak the language of business and IT.
  • Experience with data visualization tools, such as Power BI, D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, U-SQL.
  • Experience with NoSQL databases, such as MongoDB.
  • Background of IT software development a plus.
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

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