KEY ACTIVITIES
· Analyzing transactional and loyalty card data through SQL and Excel (or R / Python and other tools as required)
· Use client data to solve analytic problems related to our client’s business
· Distill key insights from customer data that address the objectives of the analysis and prepare client-ready presentations that deliver these insights effectively
· Provide actionable recommendations to improve and or/address the business question asked
· Be able to build and use segmentations, summative analyses, and predictive modeling to deliver solutions to client challenges
· Correctly QA and validation of your work and the work of others as required
· Take responsibility for the resolution of issues and problems
· Establish a close working relationship with the client team, production, and development team, collect essential information, and ensure that methodologies and processes are shared and understood.
· Process improvement through automation or integrating best practices
· Create detailed process document and QA checklist for all projects with sign-off
· Living Symphony RetailAI Values:
o We build Trusted Relationships with customers
o We openly Connect & Communicate
o We are Always Innovating
o We are Serious about Quality
o We will Win Together
o We are Enthusiastic
· No non-compliance in filling timesheet or applying leaves adhere to company policies
· Ability to work under strict deadlines with a go-getter attitude
· A high degree of self-motivation
· Flexibility - within working hours, location, and also the complexity of work
YOUR PROFILE:
· BS in Mathematics, Economics, Computer Science, Information Management or Statistics
· Data manipulation (1.5+ years) – analyzing large volumes of data in raw form and a solid understanding of database principles and efficiencies required
· Technical (1.5+ years) – Experience in using a statistical package (such as R or Python); SQL is essential and highly proficient in Excel
· Written communication skills – create a clear and concise project brief, and effectively put down the actionable insights and recommendation for the client deliverable
· Basic statistics and data science: familiarity with average, deviations, correlation, regression, and machine learning technique is expected as a minimum
· Familiarity with retail, and particularly supermarket retail data would be beneficial
· Have background with Supermarket retailers / IRI / Nielsen / dunnhumby / CPG
preferred
· Keen interest in technology
· Strong analytical and problem-solving
· Detail-oriented
· Ability to deliver well with no errors under pressure or stresses
· Be resilience i.e. able to recover yourself after any toughness / strong set-backs
Desired Skills –
o MS PowerBI
