IN Data Scientist - Artificial Intelligence

Role & responsibilities

We are looking for a highly skilled and motivated Data Scientist Artificial Intelligence to join our team in Bangalore. The ideal candidate will have strong experience in data science, machine learning, artificial intelligence, statistical modelling, and Python, with the ability to translate complex business problems into scalable AI/ML solutions. The candidate will work closely with business stakeholders, data engineers, and technology teams to develop, deploy, and optimize data-driven solutions that deliver measurable business value.

Analyze large and complex datasets to identify trends, patterns, and actionable insights.

Design, develop, and implement machine learning and AI models for business use cases.

Perform data preprocessing, feature engineering, exploratory data analysis, and model evaluation.

• Develop predictive and prescriptive analytics solutions using appropriate statistical and machine learning techniques.
• Build and optimize machine learning models using algorithms such as regression, classification, clustering, ensemble methods, and time-series techniques.
• Apply Generative AI / NLP / Deep Learning concepts where relevant to business requirements.

Evaluate model performance and continuously improve accuracy, scalability, and reliability.

• Collaborate with data engineers to ensure availability, quality, and integrity of data required for analytical solutions.

Translate business requirements into technical data science solutions and communicate findings effectively to stakeholders.

Develop reusable data science frameworks, pipelines, and analytical solutions.

• Document methodologies, assumptions, models, experiments, and results.
• Stay current with emerging AI/ML technologies, tools, and industry best practices.

Preferred candidate profile

Strong programming experience in Python.

Hands-on experience with Machine Learning and Artificial Intelligence.

Strong knowledge of:

1. Pandas, NumPy, Scikit-learn
2. Statistical analysis and predictive modelling
3. Feature engineering and model selection
4. Model validation and performance evaluation

Experience with SQL and working with structured/unstructured datasets.

Understanding of data visualization tools and techniques.

Strong analytical and problem-solving skills.

Ability to work with cross-functional teams and communicate technical concepts to non-technical stakeholders.