Data Scientist
Unilever · Bengaluru
- Experience3–4 yrs
- SalaryNot disclosed
- Work modeonsite
- Levelmid
- Posted18 Sept 2026
About Unilever
Unilever is hiring in Bengaluru in consumer goods. This role looks for around 3+ years of experience.
Skills
- Python
- Data Science
- Statistical Modeling
- Machine Learning
- Deep Learning
- Predictive Modeling
- Prescriptive Modeling
- Model Evaluation
- Data Visualization
- Software Development
- Version Control
- Model Governance
- Artificial Intelligence
The role
A data scientist at a consumer goods company develops Python models for scientific computing, machine learning and product innovation, translating complex data into predictive insights and analytical applications. The role also applies generative artificial intelligence and Google Cloud Platform to support research workflows and evidence-led decisions.
Full job description
Job Title: Data Scientist
Location: Bengaluru, India
Function: R&D
Data Scientist - Home Care Research & Development
Turn scientific data into insights, innovation and real-world impact combining data science and python modelling to connect data, models and scientific workflows, accelerate virtual experimentation and help teams make faster, evidence-led decisions.
Shape the future of innovation through data and science
At Unilever, billions of people use our products every day. Behind each innovation is a team of scientists, technologists and problem-solvers working together to improve everyday life and create a more sustainable future.
We are looking for a Data Scientist to join our Home Care Research & Development team. You will apply Python programming, data science and modelling knowledge to solve practical scientific challenges, accelerate product innovation and help teams make faster, evidence-led decisions.
If you enjoy turning complex data into meaningful insights, building reliable models and working closely with scientists, we would love to hear from you.
Why join us?
You will join a collaborative global team that brings together science, technology and creativity. In this role, you will:
Help scientists make faster and better-informed decisions.Work on meaningful applications of data science, machine learning and artificial intelligence.Develop solutions that directly support product innovation and research.Collaborate with experts across science, data, digital technology and business teams around the world.Build your technical, scientific and leadership capabilities through varied projects, mentoring and continuous learning.
What You Will Do
Partner with scientists and business colleagues to understand challenges and translate them into clear analytical questions and practical solution plans.Develop reliable Python codes for data collection, cleaning, transformation, analysis and reusable modelling workflows.Analyse structured and unstructured data using statistical, machine-learning and, deep-learning techniques.Build, validate predictive and prescriptive models, clearly documenting their assumptions, performance, limitations and suitability for use.Continuous monitoring and adoption of the applicationsDevelop user-friendly applications that enable scientists to use models and analytical solutions effectively.Create visualisations and dashboards that make complex information easier to understand and support informed decisions.Apply good software development practices, including version control, modular coding, testing and documentation.Contribute to data quality, model governance and the responsible use of artificial intelligence.Work with global teams, communicate progress and recommendations clearly, and take ownership for delivering high-quality outcomes.
What We Are Looking For
Essential qualifications and experience
A bachelor’s or master’s degree in Data science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.At least three to four years of hands-on experience in data science, scientific computing, analytics or modelling.Strong Python programming skills, including experience with widely used data analysis and machine-learning libraries.Practical experience in modelling, machine learning and model evaluation techniques.Ability to work with complex datasets, identify insights and solve open-ended problems.Clear written and verbal communication skills, with the ability to work effectively with both technical and non-technical colleagues.
Additional Experience That Would Be Valuable
Building web-based analytical applications using Python tools such as Flask, Dash or Streamlit.Working experience in GCPUsing Structured Query Language for data access and Git for version control.Creating reports and dashboards using Power BIWorking with generative artificial intelligence and large language models in scientific or business settings.Applying software development practices to create maintainable analytical products.
What Success Looks Like
You are curious, analytical and motivated by solving meaningful problems. You enjoy learning new technologies, collaborating across disciplines and turning ideas into practical solutions. You take ownership of your work, communicate openly and focus on creating value for scientists, consumers and the business.
Our team culture
You will be part of an inclusive and supportive team where different perspectives are valued. We work collaboratively, share knowledge and learn from both successes and setbacks. You will have space to contribute ideas, develop new capabilities and grow through exposure to global projects and experienced scientific and digital colleagues.
“Our commitment to Equality, Diversity & Inclusion”
Unilever embraces diversity and encourages applicants from all walks of life! This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity.
Note: "All official offers from Unilever are issued only via our Applicant Tracking System (ATS). Offers from individuals or unofficial sources may be fraudulent—please verify before proceeding."