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    Job · 18647128

    Quess IT Staffing Solutions logo

    Business Analyst - Customer Loyalty

    Quess IT Staffing Solutions · Bengaluru · hybrid · Posted 31d ago

    ₹12.0L - ₹22.0L PA2–5 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Job Role :

    • To define, develop & support analytical solutions, along with extracting insights from data for improving business decisions of various retail functions (Ex. Marketing, Merchandising, Retail etc.) in all business units of Landmark Group (LMG).
    • The recruit will be directly working with the on-shore Analytics team and with key business stakeholders of retail functions in each business unit to understand their business problems around merchandising and help deliver data driven decision making.
    • Analyze data to evaluate existing decisions framework and apply analytical techniques to discover meaningful patterns.
    • Develop and support sophisticated & innovative analytical solutions that generate actionable insights by utilizing diverse information.
    • Provide high-end consulting to functional teams to help them sharpen their business strategy.
    • Keep abreast of industry trends and emerging methodologies to continuously improve skill set.
    • Contribute to knowledge sharing and improve team productivity through training/documentation of best practices.
    • Candidate should be ready to work from office for 2 to 3 days in a week (in hybrid model)
    • Exposure to Azure Databricks (Good to have)
    • Experience in Power BI (Good to have).

    Preferred candidate profile :

    • Bachelors or masters degree in any quantitative discipline (B.Tech/M.Tech in Computer Science/IT preferred) Candidates from Economics, Statistics/Data Science or Operations Research background from reputable institutions would also be preferred
    • Ability to handle large datasets and expertise in analytical tools such as SAS, SQL, R, Python, Spark etc.
    • Expertise in analytical techniques such as Linear Regression, Logistic Regression, Cluster analysis, Market Basket Analysis, Product Bundling, Cross/Upsell Analysis etc.
    • Strong MS office skills and data visualization competence
    • Excellent verbal and written presentation skills
    • Should be able to articulate thoughts and ideas properly (structured approach should be there for problem solving)
    • Attention to detail and ability to work in high pressure environment.
    • Strong Drive and passion to deliver business impact through retail analytics.
    • Strong business acumen and ability to translate data insights into meaningful business recommendations.
    • Open to Travel (up to 20%) on need basis
    • 3 - 5 years of analytics experience in Retail/CPG industry covering at least 2 of the below mentioned areas:
    • Customer (insights/trends)
    • Campaigns/CRM
    • Loyalty
    • Marketing
    • Proven experience in delivering analytical solutions within mid to large size project teams.


    Sourced from naukri

    Skills

    Demand ForecastingAdvanced ExcelregressionclusteringCustomer SegmentationCustomer InsightBusiness Analysisimpact analysiscustomer analyticsMerchandisingLoyaltyMarketing AnalyticsRetail AnalysisCustomer AnalysisE-commerceSQLInventory Management

    About Quess IT Staffing Solutions

    Quess IT Staffing Solutions logo

    Quess IT Staffing Solutions

    1997

    29 years old

    Bangalore / Bengaluru, Karnataka

    India

    ₹6.2L PA avg

    Avg at Quess IT Staffing Solutions

    ₹12L – ₹22L PA

    This role

    About

    Magna Infotech, now Quess IT Staffing, is India’s largest IT staffing company with over 20 years of experience in staffing IT professionals in 300+ companies across levels and skillsets. Our 10,000+ associates deployed in 80+ cities and towns are proficient in over 500 technological skills.

    Industries

    AutomobileRecruitment

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    Culture

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    Career growth

    2.3

    Work-life

    2.8

    Employees rate it well for

    Work-Life Balance32Overall Company32

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