Job Description
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It With Pride.
You will help our business react to changing business conditions with excellent data analysis. You will define the requirements, perform the analysis and identify patterns in large amounts of data.
How you will contribute
You will:
- Define requirements for analysis in a given business area and perform detailed analysis and identify trends defined in the requirements
- Identify patterns and help the business react to changing business conditions
- Perform root-cause analysis and interpret data
- Work with large amounts of data such as facts, figures, and mathematics/formulas and undertake analytical activities and delivers analysis outputs in accordance with customer needs and conforming to established standards
- Understand and be involved with aspects of the data science process
- As the investigator on the data science team, you will apply your knowledge of languages and pull data out of SQL databases, using Tableau/Power BI type tools, and producing basic data visualizations and reporting dashboards
What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
- Knowledge of Microsoft Excel, Power BI, SQL,R, Python, SAS software, Google Analytics, Google Tag Manager, Tableau, Google AdWords, statistical software
- Moderate knowledge in math and statistical skills, strong business acumen, moderate computer science/coding skills
- Develop key performance indicators and create visualizations of the data
- Utilize business intelligence and analytics tool
More about this role
You will represent and communicate data requirements to help us understand our data assets and the relationships among them. You will investigate, analyze and scope data requirements to support the development of data integration, data retrieval and reusable data sets.
What you need to know about this position:
The Data Scientist will be responsible for advanced forecasting methodologies for demand forecasting to generate better forecasting results in terms of accuracy and bias
- Determine, create and maintain the best Statistical models be to be used, by considering SKU demand behavior using segmentation strategy, to generate high quality demand statistical forecast with low forecast error and bias
- Refine forecasting models, by reviewing forecast performance and incorporating feedback from the Demand Planner, to improve forecast error and bias metrics
- Analyze the model performance every month / week where MAPE (Main Absolute Percentage Error) is deteriorating and post process the output and if required finetune the output
- Propose additional strategies to have a better code (efficient or more accurate) to execute in Databricks.
- Collaborate with Demand Planners to provide explainability of models and gather feedback to improve the models
- Lead, develop, and deploy some algorithms built on databricks that help to the predictive process to be more efficient and accurate.a a high-qualitymonth/weekpost-processmore , fine-tuneDatabrickswill you bring
What extra ingredients you will bring:
- Lead the statistical forecasting process to provide the business a statistical base forecast for its demand planning process.
- Lead some continuous improvement projects to get more efficient, robust, and accurate models to predict.
- Analyse business requirements as a guide for data modelling and apply data analysis, design, modelling, and quality assurance techniques, based on a detailed understanding of business processes, to establish, modify or maintain data structures and associated components (entity descriptions, relationship descriptions, attribute definitions
- Manage the iteration, review and maintenance of data requirements and data models and you will assist in creating the sematic layer of data
- Choose a suitable data modeling approach for each project, such as by assessing the suitability of existing data models and build data models with the flexibility to change when business requirements change
- Reconcile multiple logical source models into a single, logically consistent model and you will ensure that the proposed model follows data architecture guidelines and best practices
- Design, build, implement and/or maintain Python/PySpark algorithms to execute predictive analysis which help to improve planning processes.
- Analyse code, define and implement strategies to have more accurate and efficient results
A desire to drive your future and accelerate your career and the following experience and knowledge:
- Extensive experience in data modeling in a large complex business with multiple systems
- Ability to simplify complex problems and communicate them to a broad audience
- Design, build, implement and/or maintain Python/PySpark algorithms to execute predictive analysis which help to improve planning processes.
- Analyze code, define, and implement strategies to have more accurate and efficient results
- Working in cloud computing environments with tools like databricks and help MDLZ to have better practices on it.
- Aligning and coordinating activities with different areas and stakeholder to guarantee a good execution of projects and processes.
Education / Certifications:
- Bachelor's Degree required. Masters in quantitative field of Statistics, Applied Mathematics or Engineering, with specific full-time courses in Analytics preferred
- Certifications Google Cloud Platform as Data Scientist, or Data Analyst, or in Databricks (nice to have)
- Experience in any Data Science language like Python (preferred), PySpark (preferred), R, Julia.
- Experience developing and deploying Statistical and/or machine learning solutions.
- Knowledge and experience in data science cloud platforms like Databricks (preferred) or similar.
- 10+ years of applied knowledge of analytical techniques in statistical modelling, machine learning with exposure to forecasting domain especially driver-based forecasting
- 10+ years of experience in handling multiple projects leading in the domain of supply chain and forecasting with multiple team members as part of org structure,
- Experience on working with FMCG, Food & Beverages, Retail or similar industry data with understanding the business process will be an advantage (nice to have)
- Should be able to articulate data science outcome into business understandable language
- Experience leading projects and/or processesan ,,the ,,outcomes
Business Unit Summary
Mondelēz International is the world’s largest chocolate, biscuit and candy maker, and the second largest gum maker. Our North American and U.S. headquarters are in East Hanover, New Jersey, about 25 miles outside of New York City. We have Canadian offices in Toronto and Montreal. We have a strong North American manufacturing presence where we make our well-loved snacks like Oreo cookies, belVita breakfast biscuits, Trident gum and Cadbury chocolates. Our East Hanover location also houses our global research and development center for our consumer-favorite cookie and cracker brands.
USA:
Mondelēz Global LLC is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected Veteran status, sexual orientation, gender identity, gender expression, genetic information, or any other characteristic protected by law. Applicants who require accommodation to participate in the job application process may contact 847-943-5460 for assistance.
Canada:
If you are applying to a position in Canada, accommodations for applicants with disabilities or other grounds protected by human rights legislation are available upon request for candidates taking part in all aspects of the employment selection process. For all internal and external applicants who require accommodation in the recruitment and selection process please contact 847-943-5460 for assistance/support.
Job Type
RegularData ScienceAnalytics & Data ScienceOriginally posted on