AI/ML Researcher
AkzoNobel
Bengaluru(Hoskote)0–5 yrs1h agovia Naukri
This job at a glance
- Who can apply
- Freshers and up to 5 years · Bachelor's degree or Master's degree
- Must know
- PythonData analysisPyTorchTensorFlowscikit-learnPandas
- Nice to have
- StatisticsMachine learning
- Work
- On-site in Bengaluru(Hoskote)
- Pay
- Not stated by the employer.
- Skill demand
- Python75%PyTorch43%TensorFlow39%Data analysis14%of 99 similar fresher jobs posted in India this week
- Listed
- 2 Nov 2026 · still open
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Key Responsibilities
- Analyze, clean, process, and interpret large datasets to identify patterns, trends, and meaningful insights.
- Apply statistical techniques, hypothesis testing, probability, and predictive analytics to solve research and business problems.
- Develop, train, test, and validate machine learning and statistical models using Python.
- Work on supervised and unsupervised learning techniques, including regression, classification, and clustering.
- Perform exploratory data analysis (EDA), feature engineering, model selection, and performance evaluation.
- Apply statistical modelling and experimental data analysis to support research and decision-making.
- Work with Python libraries such as Pandas, NumPy, Scikit-learn, SciPy, and TensorFlow/PyTorch.
- Work with Databricks and structured datasets for data exploration and analytical modelling.
- Collaborate with research, R&D, and technical teams to understand problems and develop data-driven solutions.
- Interpret model outcomes, validate findings, and communicate analytical insights to stakeholders.
- Document research methodologies, statistical findings, modelling approaches, and results.
Requirements & Tech Stack
- Strong knowledge of Python programming.
- Hands-on knowledge of Pandas, NumPy, and Scikit-learn.
- Good understanding of Applied Statistics, Probability, and Statistical Modelling.
- Knowledge of Regression, Classification, and Clustering techniques.
- Understanding of Machine Learning algorithms and model-building methodologies.
- Experience or academic exposure to Data Analysis, Exploratory Data Analysis (EDA), Feature Engineering, and Model Validation.
- Exposure to TensorFlow or PyTorch.
- Knowledge of Databricks.
- Familiarity with SciPy, Statsmodels, and MLflow.
- Exposure to research-oriented, industrial, or manufacturing datasets.
- Knowledge of Computer Vision and Deep Learning.
- Familiarity with Colour Science, spectral data, or R&D analytics.
Qualifications
- Master's degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or a related quantitative discipline preferred.
- Bachelor's degree in Engineering, Computer Science, Mathematics, or Statistics with strong Data Science knowledge may also be considered.
- 5-7 years of relevant experience in Data Science, Applied Statistics, Machine Learning, or Research Analytics preferred.
- Freshers with a Master's degree and strong academic knowledge or hands-on project experience in Data Science, Statistics, and Machine Learning are also encouraged to apply.
- Candidates should demonstrate strong fundamentals in statistical analysis, Python programming, and model development.
- Freshers with relevant Master's qualifications, strong coursework, and practical Data Science projects are welcome to apply.