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Data Analytics:

Mondelez
Location: Mumbai,Pune, Experience: 2 years - 10 years
Posted On: 08-Dec-2021 | Last Date to Apply: 12-Feb-2022 | No: of Vacancies : 10

Company Profile:

Central Analytics Team at Mondelez International provides visibility, insights and solutions across the globe to different supply chain pillar teams in order to help the organization make better decisions. This is a rapidly growing and fun team with talented people of diverse experiences and cultures. If you have the passion to solve complex business problems and create an impact, then we have an opportunity for you.

Job description:

CAT Team

Central Analytics Team at Mondelez International provides visibility, insights and solutions across the globe to different supply chain pillar teams in order to help the organization make better decisions. This is a rapidly growing and fun team with talented people of diverse experiences and cultures. If you have the passion to solve complex business problems and create an impact, then we have an opportunity for you. Please apply through this link.

Job Profile:

You will be crucial in supporting our business by creating valuable, actionable insights about the data, and communicating your findings to the business.  You will work with various stakeholders to determine how to use business data for business solutions/insights.

 

How you will contribute

You will:

  • Partner with North America Manufacturing Analytics leaders to understand the roadmap and provide support defining the scope of different initiatives and business problem statements.
  • Identify/formulate the specific analytics problem statement based on the business inputs, data analysis and hypothesis testing to drive value for the organization.
  • Provide visibility of key performance indictors to the leaders by developing reports and dashboards.
  • Understand business challenges, collect, cleanse, and analyze the data to identify trends and insights for the business to provide actionable insights that drives differential actions and decision making.
  • Create customer models or prototypes to test the hypothesis and make recommendations towards scaling the solution.
  • Lead design and development of the analytical solutions around different workstreams and initiatives (such as Waste, Quality, Reliability, Long Term Capacity Strategy, Workforce planning etc)
  • Collaborate with the various analytics and business partners to drive the successful execution of solutions development.
  • Analyse and drive value from data through various analytics approaches of descriptive, predictive and prescriptive analytics using visualization, predictive modelling and OR techniques. 

 

What you need to know about this position:

This role will be responsible for evaluating the specific needs of analytics, assess the problems to be solved and what data points to use and apply appropriate analytical methods by analysing data, generating insights, and developing solutions to create value and support decision making for Manufacturing domain.

What skillsets need for this position:

  • Should be well verse with handling large scale data sets and work with data coming from various systems.
  • Expertise on the tools such as Alteryx, Tableau, R, R Shiny, Python
  • Strong concepts and experience around statistics, SPC, applied mathematics
  • Understanding of manufacturing/operations concepts will be desired
  • Knowledge of different database solutions will be desired.

 

Education / Certifications / Experience Requirements

    • Bachelor’s degree, in a quantitative field such as Statistics, Applied Mathematics, Industrial Engineering, Data Science, Operations Research
    • 3-10 years of work experience in analytics, consulting and solutions development
    • Experience in support of Manufacturing, Engineering and Operations will be a plus

 

Key Qualifications

Bachelors

Education

Any Bachelors Degree

Skills

Alteryx,Tableau,R,R Shiny,Python,SPC,applied mathematics,

Industry

FMCG/Food/Beverage

Gender Preference:

Female

Job Type:

Full Time

Diversity Tags:

Not Applicable