About The Position

The Analyst role focuses on providing solutions to clients utilizing advanced analytics tools. A successful candidate for this role will have knowledge of primary and secondary market research data deliverables. This is the ideal role for someone who is client facing, is collaborative, self-motivated, client focused and has a proven record of successful implementation of out-of-the-box solutions.

Requirements

  • Bachelor’s degree in science (IT), B. Tech (IT), M. SC (IT), master’s in computer applications (MCA), Post Graduation Diploma in Data Science.
  • Minimum 2 years of experience in advanced analytics.
  • Exceptional ability to multitask and balance multiple projects and priorities.
  • Strong problem-solving skills, including an ability to ‘think outside the box.’
  • Strong communication skills across variety of stakeholders.

Nice To Haves

  • MS Office experience (Excel, Word, PPT)
  • Sawtooth or similar platform knowledge
  • Knowledge of platforms relevant to data services -- examples are SPSS and Python
  • Market research experience (preferably with healthcare surveys)
  • Organized, self-motivated and self-directed.
  • Ingenuity, with a willingness and enthusiasm for learning new techniques.
  • Excellent interpersonal communication skills

Responsibilities

  • Thorough review of client materials and preparation of queries in a timely manner.
  • Assist in building analysis plan using Sawtooth/Excel.
  • Deliverables include advance analytics solutions such as maxdiff, conjoint, TURF analysis, etc..
  • Deliver against assigned tasks in timely and high-quality manner.
  • Ensure end-to-end project delivery in alignment with Client and Operations, leading to high satisfaction.
  • Utilize their past experiences to support process improvement, with a goal to increase capabilities, efficiencies, skillsets, and competitive advantage in the marketplace.
  • Expected to spend time reporting and receiving information to and from their manager and committed to learning the latest technologies in the data collection field.
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