Data Scientist (Job Number: 1700092Y) - Unilever

Job Reference: HH100
Employer/Agency: Unilever
Location: Singapore
Salary/Package: On application
Job Sector: General Management & Consulting
Date Posted:
Closing Date:

Unilever is one of the world’s leading suppliers of Food, Home and Personal Care products with sales in over 190 countries and reaching 2 billion consumers a day. It has 172,000 employees and generated sales of €48.4 billion in 2014. Over half (57%) of the company’s footprint is in developing and emerging markets. Unilever has more than 400 brands found in homes around the world, including Persil, Dove, Knorr, Domestos, Hellmann’s, Lipton, Wall’s, PG Tips, Ben & Jerry’s, Marmite, Magnum and Lynx.

Unilever’s Sustainable Living Plan (USLP) commits to:

• Decoupling growth from environmental impact.
• Helping more than a billion people take action to improve their health and well-being.
• Enhancing the livelihoods of millions of people by 2020.

Unilever was ranked number one in its sector in the 2014 Dow Jones Sustainability Index. In the FTSE4Good Index, it achieved the highest environmental score of 5. It led the list of Global Corporate Sustainability Leaders in the 2014 GlobeScan/SustainAbility annual survey for the fourth year running, and in 2015 was ranked the most sustainable food and beverage company in Oxfam’s Behind the Brands Scorecard.

Unilever has been named in LinkedIn’s Top 3 most sought-after employers across all sectors.

For more information about Unilever and its brands, please visit For more information on the USLP:

JOB TITLE: Data Scientist
RELOCATION TERMS: Local Terms only

Position Summary
This is an exciting new role in the Analytics Capability group in Information & Analytics, which is tasked with the mandate to drive Analytics @ Scale across Markets, Functions and Categories in Unilever. The role has two main accountabilities

1. Helps business and functional leaders structure their problem statement (for analytics solutioning). Gathers, analyzes and models data to solve and address complex business problems and evaluate scenarios to make predictions on future outcomes and support decision making.
2. Create an Analytics @ Scale capability
a. Designs and drives the creation of new standards and best practices in the use of statistical data modelling, big data and optimization tools
b. Collaborates across the wider data science team to develop reusable analytics products/ assets

Expected Work
The vision for the Analytics Capability group is to grow the business with smarter decisions enabled by analytics. The team is organised in Hub and Spoke arrangement; the Spokes partnering with the business units on analytics agenda and accountable to them for quality delivery of agreed capabilities on time in full. The Hub brings in the @ scale component including an effective data science delivery capability, analytics R&D and building re-usable analytics assets.

This role will be a key constituent of Singapore Analytics Hub, which will be accountable for driving scaled analytic solutions across functions and markets.

Specifically this role will develop scaled analytic solutions to business problems using data analysis, data mining, optimization tools, and machine learning techniques and statistics that can be effectively re-applied across categories.

Key Accountabilities/Deliverables
• Implements solutions to problems using data analysis, data mining, optimization tools, and machine learning techniques and statistics
• Build data-science and technology based algorithmic solutions to address business needs
• Design large scale models using Logistic Regression, Linear Models Family, Conjoint Analysis, Spatial models, Time-series models, Text mining
• Drive the collection of new data and the refinement of existing data sources
• Analyze and interpret the results of analytics experiments
• Develop best practices for instrumentation and experimentation and communicate those to wider analytics team
• Manage and develop 1 intern (Lead recruiting future talent)
• Applies a global approach to analytical solutions-both within a business area and across the enterprise
The position will have 1 intern and own priority setting for contract employees and external resources working for third party providers.

Key Skills Required
Professional Skills
Analytics Modelling & Techniques Fully Operational
Data Exploitation Fully Operational
I&A Technology Working Knowledge
Data Visualisation Fully Operational
Product Lifestyle Management Working Knowledge

Relevant Experience:
• B.S. or M.S. in a relevant technical field. Overall experience of 2-3+ years preferred
• Experience solving analytical problems using quantitative approaches
• Passion for empirical research and for answering hard questions with data
• Ability to manipulate and analyse complex, high-volume, high-dimensionality data from varying sources
• Ability to apply a flexible analytic approach that allows for results at varying levels of precision
• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
• Expert knowledge of an analysis tool such as R, Matlab, or SAS
• Experience working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, etc.)
• Familiarity with relational databases and SQL

As part of the application process, you will be asked to complete an online assessment consisting of 2 questions.
This is an important part of our application procedure and will take approximately 2 minutes of your time to complete. When filled out partially or not at all it may adversely affect the progress of your application.

If you encounter any issues, contact Unilever HR Services at 800-448-1479 / +65 6818-5255.

Please apply online by clicking on “Apply Online” below. Your application will be reviewed against our requirements. Should you not meet our immediate requirements, your profile will be registered in our talent pool system and we will match your profile to suitable future vacancies.

You will be able to access your status update through the candidate tracking link.

Thank you for your interest and application.

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