User:CRScribes/sandbox
A data scientist is a fusion between an information engineer and storyteller[1] . The data scientist delves into the vast amounts of data collected in a business. They use data mining techniques to find important patterns in that data, analyze the data, conceive innovative ways to use and understand the data, and then present their insights to the business end of the company as actionable intelligence that can be used to move the company forward successfully[2] . Data scientists have many similarities with statisticians, data engineers, computer programmers and others in the computer science and data management fields, yet actually combines all of those skills together into a single competitive intelligence package[3] . The growth of big data around the world has made this position a must have for many enterprises since the data scientist is an expert at working with big data structures[4][5] .
Skills
[edit]- Computational mathematics
- Statistical Analysis
- Knowledge of machine learning
- Computer programming/scripting skills - especially C/C++, Perl, Python, Java and others
- Good understanding of relational databases and SQL
- Experience with NLP or text processing
- Knowledge and experience with NoSQL and other non-relational database systems and tools
- Data mining experience
- Understanding of data modeling methodologies and techniques
- Knowledge of visualization software and techniques
- General understanding of distributed computing architectures
General Skills[8]
- Good business acumen - must understand the monetary potential of the data
- Excellent communication skills to effectively speak with business users and C-Level Executives
- Strong ability to be innovative and creative with data
- Ability to tell a story through data
- Ability to model, predict, and classify consumer behaviors and other business metrics
- Strong organizational skills
- Must have strong logical and analytical thought processes
- Close attention to detail while also understanding the big picture and impact of data across all of the systems within the corporation
- Work well in a team
Education/Certification
- At minimum a B.S in Applied Mathematics, Computer Science, Engineering, Operations Research, Statistics or related field
- Preferred M.S or PhD in one or more of those fields
- 3-5+ years of experience in the field
- Any computer-related certifications that would add to relevant skills
Duties
[edit]The specific duties of a data scientist are highly dependent on the company they work for, those listed below show a range of those abilities:[9] [10]
- Draw insights from data to help business be more successful in the marketplace
- Collect, analyze, deliver data with an actionable plan for utilizing its potential
- Create metrics and track processes to help measure the effectiveness of data modeling efforts
- Utilize data mining techniques and information retrieval methods to gather business intelligence
- Write custom scripts to cleanse, transform and normalize large data sets
- Performance tune data-centric applications to maximum optimization
- Create innovative data products that help leverage big data and analytics.
- Translate business requirements and needs into technical language so that other data specialists can help produce and conduct advanced data analysis, solutions, algorithms and other technical necessities to drive the business forward
- Identify new data sources to improve business potential
- Develop innovative metrics and predictive performance applications to measure business accomplishment
- Establish links with existing data warehouse and other sources and find new, innovative amalgamations
- Coordinate data resource requirements between analytics, engineering and business teams
- Create visualizations that clearly present the complex data relationships and discoveries for non-technical business users
See Also
[edit]References
[edit]- ^ Bhambhri, Anjul. "The Data Scientist: An Emerging Career in Data Management". Dataversity.net. Retrieved 27 March 2012.
- ^ EMC2.com. "Data Science Revealed: A Data-Driven Glimpse into a Burgeoning New Field" (PDF). EMC2 Worldwide. Retrieved 26 March 2012.
{{cite web}}: CS1 maint: numeric names: authors list (link) - ^ Patil, D.J. "Building Data Science Teams". O’Reilly Radar. Retrieved 26 March 2012.
- ^ Bates, Chris. "Big Data is Useless without Science". Kontagent Kaleidoscope. Retrieved 28 March 2012.
- ^ Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A. H.,. "Big data: The next frontier for innovation, competition, and productivity". McKinsey Global Institute. Retrieved 26 March 2012.
{{cite web}}: CS1 maint: extra punctuation (link) CS1 maint: multiple names: authors list (link) - ^ Roe, Charles. "So you want to be a Data Scientist?"". Dataversity.net. Retrieved 31 March 2012.
- ^ The Data Scientist. "Essential Tools for a Data Scientist". The Data Scientist. Retrieved 27 March 2012.
- ^ Woods, Dan. "Amazon's John Rauser on 'What Is a Data Scientist?". Forbes. Retrieved 29 March 2012.
- ^ Loukides, Mike. "What is data science?"". O’Reilly Radar. Retrieved 29 March 2012.
- ^ Woods, Dan. "bitly's Hilary Mason on 'What is A Data Scientist?". Forbes. Retrieved 29 March 2012.