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

The Data Scientist role is responsible for evangelizing the adoption of data driven decisions across Mars by leading the development of advanced analytical tools that utilize the vast amounts of data available to the company. These tools will be rooted in a strong statistical foundation and leverage cutting-edge machine learning concepts to provide actionable insights for solving business problems or finding opportunities for profitable growth.

You will be required to have proficient knowledge and strong experience in the interconnected disciplines of Applied Data Science, Optimization, AI/ML, and Operations Research. You are a strong engineer with deep expertise in cutting-edge technologies, robust design, development, coding, and testing of high-standard and scalable solutions.

You will lead efforts to translate complex datasets and mission-critical business challenges into technical problems and solve them at scale using the appropriate methodologies and tools. Your deep expertise in data analytics, AI/ML, and optimization algorithms, as well as strong practical experience with modern engineering technologies will enable you and the team to intelligently transform data into value, innovate, create high-standard robust production capabilities and deliver increased business benefits.

Day-to-day you will work in multidisciplinary teams & collaborate with Mars Global Analytics, Big Data Engineering, and Advanced ML teams. As part of your role, you will also be expected to solve problems in close collaboration with users from our business segments & markets around the world. This provides you the opportunity to be influential in establishing new & emerging capabilities that Mars needs to develop to keep pace with current trends and adopt to changing times.

What are we looking for?

• Bachelor’s degree in Analytics or related quantitative fields (Statistics, Operations Research, Mathematics, Econometrics etc.) Advanced degree is preferred.
• Minimum 3 years of experience in an Applied Data Science role or equivalent, ideally within the CPG, Consumer Products, Retail, Telecom, or Financial Services industries.
• Solid knowledge of, and experience with, modeling techniques such as Regression/GLM, Random Forest, Boosting, Deep Learning, text mining, social network analysis, and concepts of significance testing.
• Hands-on experience using tools like Python (incl. tensorflow, PyTorch, Pandas), PySpark, Scala, R; experience querying databases (SQL, Hive) and working with big data platforms such as a Hadoop ecosystem and Apache Spark; knowledge of the Microsoft Azure Stack is an advantage.
• Experience with data visualization tools such as matplotlib, Seaborn, Tableau, Power BI, D3, ggplot, plotly.
• Experience with DevOps principles such as CI/CD, unit testing, and AGILE development.
• Experience using key external third-party data sources including Nielsen/ IRI/ Storeviews, Kantar, Homescan Panel, Shopper card, and/or other first party data and consumer surveys.
• Strong problem solving, communication, presentation, and stakeholder engagement skills.

What will be your key responsibilities?

• Solve complex business problems by implementing end-to-end ML capabilities: from data exploration, model training and validation to model persistence and deployment of productionized machine learning models
• Fundamentally change the way Mars does business by show-casing the “Art of the Possible” & through the establishment of innovative data science standards and methodologies: developing scalable and sustainable solutions for diverse business segments; incorporating emerging technologies into data analysis processes and influencing the scope and direction of new projects.
• Conduct advanced statistical analyses of structured and unstructured datasets using a variety of modelling techniques, such as: linear regression, time-series, classification, neural networks (incl. CNNs, RNNs), decision trees, gradient boosting, and others to deploy interpretable products that generate insights, increase efficiency and/or enhance quality.
• Understand complex business processes and combine your business acumen, problem solving skills, and curiosity to identify value-add opportunities for the applications of statistical analyses and Machine Learning.
• Present results in a cohesive, intuitive, and concise manner that can be understood by both technical and non-technical audiences.
• Provide expertise on statistical and mathematical concepts to key 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.

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