AI/ML Researcher

Job Title: AI/ML Researcher Data Science

Location: Bangalore

Experience:57 Years | Freshers can also apply

Job Family: Technology

1. Key Purpose of the Role

We are looking for a research-oriented Data Scientist with strong expertise in Python, Applied Statistics and Machine Learning. The role involves analysing complex datasets, applying statistical techniques, developing predictive models and generating data-driven insights to solve business, research and R&D challenges, particularly in the colour and coatings domain.

The ideal candidate should have strong fundamentals in Data Science, statistical modelling, machine learning algorithms and hands-on Python programming, with the ability to conduct research, experiment with different methodologies and develop reliable analytical models.

2. Roles & Responsibilities

• Analyse, 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.

3. Role Requirements

Educational 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.

Experience

• 57 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.

Mandatory Technical Skills

• 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.

Good to Have

• 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.

4. Ideal Candidate Profile

A research-oriented Data Scientist with strong statistical fundamentals, excellent Python knowledge and practical experience in developing predictive and statistical models.

The candidate should be comfortable working with complex datasets, conducting independent analysis, experimenting with different modelling techniques and deriving meaningful insights.

Core Focus Areas: Data Science | Applied Statistics | Python | Machine Learning | Statistical Modelling | Model Building

Freshers with relevant Master's qualifications, strong coursework and practical Data Science projects are welcome to apply.