Established in 1991, Collabera has been a leader in IT staffing for over 22 years and is one of the largest diversity IT staffing firms in the industry. As a half a billion dollar IT company, with more than 9,000 professionals across 30+ offices, Collabera offers comprehensive, cost-effective IT staffing & IT Services. We provide services to Fortune 500 and mid-size companies to meet their talent needs with high quality IT resources through Staff Augmentation, Global Talent Management, Value Added Services through CLASS (Competency Leveraged Advanced Staffing & Solutions) Permanent Placement Services and Vendor Management Programs.
Collabera recognizes true potential of human capital and provides people the right opportunities for growth and professional excellence. Collabera offers a full range of benefits to its employees including paid vacations, holidays, personal days, Medical, Dental and Vision insurance, 401K retirement savings plan, Life Insurance, Disability Insurance.
• Candidates need five+ years of experience.
• Also, manager is not interested in candidates with primarily consultant experience/backgrounds.
• Desires candidates with hands on experience.
• Experience with writing scripts in SQL(Standard Query Language)
• Experience with multiple programming languages and analytic tools such as SAS, R Programming Language, and/or Tableau
• Experience with statistical analysis and /or data analytics methods Good communication skills. Minimum of 4 years education in Bachelor of Engineering such as Reliability, Mechanical, Electrical, Industrial, or equal amount of experience.
• Analytical / problem Solving Skills In Any Of The Following Areas:
• Field Reliability Data Analysis
• Design for Reliability (DFR)
• Root Cause Analysis (RCA)
• Failure Mode and Effects Analysis (FMEA)
• Design of Experiments (DOE)
• Degradation Data Analysis
• Statistical Data Analysis.
• Experience with Telematics Data (Diagnostic Trouble Codes, Machine/Engine Operating Conditions data).
• Develop specific analysis reports and solutions for identifying patterns or trends related to reliability performance using Telematics data.
