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Data Scientist

Place of work
Digital Park II, Einsteinova, Petržalka
Contract type
full-time
Wage (gross)
2 400 EUR/month

Information about the position

Job description, responsibilities and duties

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 ML
  • A natural inclination toward solving complex problems
Knowledge/experience with statistical programming languages including SAS, R, Python, SQL, etc., to process data and gain insights from it
  • Knowledge of machine learning techniques including decision-tree learning (Random Forest, Gradient Boost) 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
  • 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

Employee perks, benefits

We offer a highly competitive salary plus annual bonus payment based on your performance.
We also offer top attractive benefits, such as:

  • Yearly salary review based on performance
  • Supplementary pension fund
  • Flexible working hours
  • Company notebook for private use
  • Home office benefit policy
  • Extra holidays
  • Paid days off (childbirth, birthday, wedding, etc.)
  • Sick days
  • Sick leave allowance
  • Electronic meal voucher card fully covered by employer
  • Free drinks, fruit and company products in the workplace
  • Company products with discount to please your family members and friends
  • Contribution to well-being (sports, relax, culture, travelling, etc.) via Cafeteria
  • MultiSport card for leisure activities
  • Contribution to healthcare (rehabilitation, opticians, pharmacies, etc.)
  • Year-long healthcare or preventive health check-up
  • Service awards
  • Company gym
  • Contribution to wedding, childbirth and retirement
  • Life insurance
  • Long terms sick leave and dread diseases insurance
  • Company parties and team events
  • International environment and further career progression
  • Contribution to education and ACCA study
  • Constant virtual and F2F learning opportunities

In case of selected positions also:

  • Company car for private use
  • Company cell phone for private use

Requirements for the employee

Candidates with education suit the position

University education (Bachelor's degree)
University education (Master's degree)
Postgraduate (Doctorate)

Language skills

English - Advanced (C1)

Personality requirements and skills

What you need to know about this position:

The Data Scientist forecasting 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
  • Collaborate with Demand Planners to identify right drivers and lever which influences demand and thus incorporate in statistical forecasting process
  • Support SAS Implementation for market for demand modelling in SAS and SAS Model Forecast Improvement activity. Keep close liaison with SAS implementation partner to get transitioned process to Central Analytics Team
  • 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 is deteriorating etc) and post process the output and if required finetune the output
  • Propose additional data elements which we can consume and work with ETL developer to get those into SAS staging and SAS ABTs
  • Run demand-supply segmentation analysis as per defined frequency

Education / Certifications

Either of the following is applicable as educational criteria for the position:
  • Degree/Masters in quantitative field of Statistics, Applied Mathematics or Engineering, with specific full-time courses in Analytics
  • Certifications any of SAS Base, SAS VF, SAS Visual Statistics, etc
  • Strong Applied Knowledge of analytical techniques in statistical modelling, machine learning with exposure to forecasting domain especially driver based forecasting
  • Experience on working with FMCG, Food & Beverages, Retail or similar industry data with understanding the business process with be advantage
  • Should be able to articulate data science outcome into business understandable language
  • Fluent English, other European languages would be an advantage.

Advertiser

Brief description of the company

Mondelēz International Inc. empowers people to snack right in over 160 countries around the world. We’re leading the future of snacking with iconic brands such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. Our 90,000+ colleagues around the world are key to the success of our business. Great people and great brands. That’s who we are.

Join us on our mission to continue leading the future of snacking around the world by offering the right snack, for the right moment, made the right way.

Number of employees

500-999 employees

Company address

Mondelez European Business Services Centre s.r.o.
Digital Park II, Einsteinova 19
851 01 Bratislava
Slovensko / Slovakia
careers.mondelezinternational.com

Contact

Kontaktná osoba: Nicholas Murray
E-mail: poslať životopis
ID: 4181128  Dátum zverejnenia: 12.10.2021  Základná zložka mzdy (brutto): 2 400 EUR/month