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We are looking to hire an Associate Data Scientist, Modelling & Analytics Digital R&D based in Bangalore
Unilever is one of the world’s leading suppliers of fast-moving consumer goods. Our products are sold in over 190 countries and used by 2 billion consumers every day. People know us by our brands which include Dove, Suave, Lifebuoy, Axe, 7th Generation, Knorr, and Ben & Jerry’s ice-cream. Unilever has extensive R&D facilities around the globe with a mission to innovate boldly for people and planet. To meet the sustainable business growth challenges of the next decade, Unilever R&D aims to transform its approach to scientific discovery and product development, through a Digital Transformation program. The Digital R&D team is leading this transformation of R&D through programs focused on Digitalization of R&D (knowledge/insights discovery, virtual product design and simulation) and developing Digitally enabled consumer innovations. The Modelling & Analytics team in Digital R&D, is a central expertise team that provides leading edge statistics, data science, data management, modelling and simulation expertise to deliver predictive models and advanced analytics for new insights to the category programs across all R&D functions. The products and brands we support are across Unilever’s categories in Foods & Refreshment, Home Care and Beauty & Personal Care.
We are looking for a Data Scientist who will support our Product Innovation and Science & Technology teams in R&D with insights gained from analyzing data. The ideal candidate is adept at using large biology data sets to find functional insights of various biological processes. The candidate should also apply the analytics for product and process optimization and use models to test the effectiveness of different courses of action. Must have strong background in analyzing omics datasets using relevant tools and databases for human biology and microbiome. Experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Engagement and collaboration with globally deployed, multi-disciplinary teams to design and implement efficient, well-focused, statistically fit-for-purpose studies, analyse, visualize and interpret data, build and validate models and simulations.
- Work primarily with Biology teams to design experiments, carry out multi-omics data analysis. Should have sound working knowledge of cheminformatics, microbiomics and network biology.
- Build mathematical and statistical models for biological and other related datasets. Application of ML/AI techniques, deep learning methods and network science to drive innovations in biology/non-biology dataset including image data.
- Build capabilities to be democratized and carry-out upskilling sessions to non-experts.
- Should work in inter-disciplinary teams that will include product formulators, process/packaging engineers, clinicians, measurement scientists, bio-informaticians, claim experts, and other data scientists, both internal to Unilever and external partners.
- Demonstrate agility by extending the analytics skills application beyond biology dataset.
- Candidate must be able to communicate the analytical results and insights effectively with the program manager and senior management.
The candidate should have a Master’s Degree and 6-9 experience in Computational Biology/ Data Science or equivalent. Experience in FMCG/Retail/Pharmaceutical industries is a plus.
- Technical depth, operational breadth and demonstrated fluency in applying bioinformatics/data science for scientific research.
- In-depth experience in analyzing transcriptomics, microbiomics, interactomics and proteiomics data.
- Well-versed with multi-omics analysis capability.
- Knowledge of systems level functional analysis of biological data.
- Proficiency in network science and usage of networks analysis and visualization tools and databases.
- Working knowledge of ML/AI techniques and applications, understanding of NLP algorithms and image analytics.
- Programming skills: Python and R (High proficiency required). Experience developing R-Shiny/ Python-Dash apps and working knowledge of Power BI is beneficial but not compulsory.
- Strong scientific written and communication skills
Connect with us
We’re always looking to connect with those who share an interest in a sustainable future.
Get in touch with Unilever PLC and specialist teams in our headquarters, or find contacts around the world.Contact us