Crayon Data - Business Analyst

Purpose of the role:

- The Business Analyst is expected to work in different environments such as - deliver product led services to key customers across the globe, take product initiatives, new solution development initiatives etc.

- Key responsibilities of this role are - ensuring overall delivery quality, incident management, ongoing service improvement and ensuring a high degree client satisfaction.

Key Responsibilities of the role:

- Understanding/experience in developing business requirements, defining the ‘possible applications using the data universe’, and recognising limitations of data & its uses.

- Successful project delivery - high degree of client satisfaction and project objective completion

- Understand client objectives and requirements and create a workable delivery plan. Delivery plan to cover all aspects of project management, data acquisition, analytics, end user flow etc.

- Provide direction, support, guidance and collaborate with a team of business analysts, data miners, data analysts and the technology team to ensure successful project delivery

- Interact with client delivery and crayon client engagement teams to ensure that no gaps exist between client requirements and delivery plan

- Overall ownership of all internal and external initiatives required to drive successful project completion

Key skills/qualification for this role:

- 2-5 years of experience in client facing product or product driven service delivery roles

- Knowledge of business functions like Marketing, Market Research, Sales & Marketing, Customer Relationship Management will be extremely useful.

- In-depth knowledge in one or more of the following subject matter areas preferred: business intelligence, analytics, data driven decision making and strategy/management consulting

- Strong leadership and collaboration skills including the ability to develop, influence and motivate a team and peers to maximize results

- Working knowledge/exposure to data analytics packages such as R, SAS, SPSS etc.

- Ability to synthesize data driven insights from large data sets – both qualitative and quantitative.

- Knowledge of the SDLC and ability to understand technical requirements, constraints, methodologies etc.