Senior Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

• Enthused to boost your teams journey with your digital skills?
• Inspired to be part of the team that digitally reimagines the way we work at Mars?
• Want to practice your digital muscle and ability to engage others on the journey?

Mars is setting up the Centre of Excellence, the driving force of a human centric digital planning transformation.
Want to be part of this uplifting transformation by creating the digital network to connect all planning processes? Read more below….

CONTEXT &THE TEAM

In this rapidly changing world, an agile supply chain (SC) makes the difference for our customer and consumers. Mars believes that a human centric and digitally connected planning team is key to unlock this as it is the glue for ONE end to end SC team. With “enterprise planning” Mars is initiating this new planning team creating a whole new organisational structure, future fit planning capabilities & processes and underlying best in class systems. It transforms the way Mars SC works: more connected, transparent, faster, agile, customer focused and digital. In short an exciting human centric, digital transformation journey for the whole Mars SC.

The (Planning) Center of Excellence -CoE- sits at the heart of this transformation. It can be seen as a digital catalyst to speed up and strengthen the planning transformation. The team services both the European and the Russian sourcing circle. It will operate by the principals of: full transparency of processes and data, planning by exception and continuous improvement of people processes and systems. In practice this means a build-measure-learn approach that is implemented through:

• monitor (adopted) planning ways of working,
• provide action driven insights to the business
• identify best practices internal and external,
• build new capabilities, processes, tools and dashboards,
• create a machine driven forecast as a common point of reference
• store and retrieve the right data with appropriate quality checks
• provide training for tools and ways of working

As this transforms the way of working in Mars the CoE is looking to create a strong dynamic team of digital savvy and content heavy change agents. We will share the common passion to bring the benefits of a digital way of working to the people in the (planning) operation all around Europe for their own benefit and that of customers / consumers.

THE ROLE

In this team the Snior Data Scientist is part of the insights & analytics team. The team is building the data driven decision making muscle in the planning teams in Russian and European sourcing circles. This is a technical a process as well as a people challenge. Technical because: the data needs to be gathered in a way that can be easily reused in the future (data infrastructure), the statistical analytics and forecasting tools need to be optimised and the reporting dashboards provide a real time intuitive summary. A people challenge because: the real problem can only be understood by engaging with the business users; to drive data quality starts with engaging people to enter the correct data on time and to provide a trusted solution required to create a userfriendly and intuitive user interface. To face this challenges the senor data analyst is working together with multiple teams that will help with the process knowledge and the stakeholder engagement the data analyst collaborates on these topics and gives guidance through his/her data insights and then leads the technical solutioning where needed. Next to this they will have a key role in leading and influencing the rest of the E2E Planning organisation and adjacent functions (such as Digital Technology) to drive the MW Supply Chain Data and digitalisation Strategy. Key elements of this will be defining the data structure, codesigning the data infrastructure, create a processlake i.e. a digital space where the status of all planning related processes can be followed, create workspaces (UI) that are intuitive and can de continuously improved,…. on reports that can be continuously improved at low cost, ….

In this way the ideal data scientist has a strong technical profile that extends all the way into long term data structure and infrastructure knowledge with high business acumen and a passion to help people utilise digital tools.

In practice this means the role has 5 key elements that are based on continuous improvement: 1. emerge themselves in the business problems to clarify the essence and agree priority. 2. Build the required and reusable data infrastructure for the best analysis 3. Solve data issues through technology or organisational alignment 4. Co-develop a repetitive mechanisme to analyse and solve the problem. 5. Repeat the cycle.
Additionally, the senior data scientist will continuously monitor if the development routes chosen are future fit and in line with the chosen strategy. If there is a misfit he will reassess the project and or the strategy as needed and pull together the relevant parties to do so.

Key to this is to ensure that the (statistical forecast) solution is communicated and explained to the markets / planning team in a non-technical way to ensure the (forecast) result is accepted and not overwritten. This requires the ability to listen to market feedback, evaluate statistical findings / improvements, provide business insights on different level a aggregation and clearly communicate to stakeholders in their language.

The key results the senior data analysts is measured against are: (internal) customer engagement scores (including reference score and useage frequency of reports; uptime of reports); improvement of technical forecast accuracy, correct segmentation of portfolio between machine and human forecasting (ideally this leads to a 60-80% machine forecasted portfolio) and lead time for report amendment/creation.

They will achieve this by developing a strategy to assess and mine data, utilising internal and external data sources. They will manage requests and collaborate with associates in markets, planning teams and 3rd party providers as needed.

As this is a complete new way of planning in Mars this approach will to evolve over time. The data scientist will need to amend his leadership and stakeholder management style to this. Especially in the beginning it will be crucial to be able to bridge the gap between statistics and standard business way of working

What are we looking for?

Education and Professional

• S. or BA in computer science, data science, machine learning, mathematics, statistics or related natural science or technical degree. Master or advanced degree preferred
• 5 years of experience working in a technical / analytics role

Knowledge / Experience

• Experience in a programming language such as R or Python
• Experience with data structures (SQL, Azure)
• Experience with ERP and Advanced Planning Systems (preferably E2Open or RapidResponse)
• Understanding of Lean / Six Sigma / root cause analysis, e.g., 5 why’s
• Ability to support complex analysis in understandable forms to business stakeholders
• Attention to detail and a passion for data accuracy
• Fluent in English
• Strong expertise in combination of Mathematics, Statistics, Business acumen and programming

What will be your key responsibilities?

• Define focused value added planning problem-statements for balancing service, stock and cost for the business based on use-cases, design thinking and value stream analysis.
• Providing insights from data to support the organization making more and more data driven decisions in the area of: forecasting, supply planning, risk analyst in supply & demand, inventory setting
• Presenting results in a compelling and clear manner to drive business decision making
• Supports demand sensing activities in E2Open through the provision of analysis and insights to optimize forecasting results
• Build algorithms and design experiments to merge, manage, interrogate, and extract good quality data needed for this.
• Look for opportunities to improve the flow of data and evaluate new and emerging technologies
• Identifying new relevant data sources and incorporating these in the data structure.
• Enhancing data collection procedures to create new data sources
• Expert in understanding data model types to identify and decide which one to use and be able to align these insights to internal and external stakeholders

What can you expect from Mars?

• Work with over 130,000 like-minded and talented Associates, all guided by The Five Principles.
• Join a purpose driven company, where we’re striving to build the world we want tomorrow, today.
• Best-in-class learning and development support from day one, including access to our in-house Mars University.
• An industry competitive salary and benefits package, including company bonus.