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 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:
- Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization. In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modeling
- Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business. After that you will work with stakeholders to determine how to use business data for business solutions/insights
- Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor results
- Apply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data
- Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy
- Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making
- Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements
What You Will Bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
- Strong quantitative skillset with experience in statistics and linear algebra.
- A natural inclination toward solving complex problems
- Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it
- Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons
- Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc.
- Good communication skills to promote cross-team collaboration
- Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc.
- Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholders
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 a segmentation strategy, to generate high 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, fine-tune 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 the predictive process to be more efficient and accurate.
What extra ingredients you will bring:
- Lead statistical forecasting process to provide business a statistical base forecast for its demand planning process.
- Lead some continuous improvement projects to get a more efficient, robust, and accurate models to predict.
- Analyze business requirements as a guide for data modeling and apply data analysis, design, modeling, 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 processes
- Fluent English is a must
Job specific requirements:
Travel requirements:
Work schedule:
Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy
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
Regular
Data Science
Analytics & Data Science
