To be successful as a Data Scientist you should have experience with:
Essential Skills
- Solid understanding of machine learning concepts and model deployment.
- Prior experience in a data science role, indicating a strong foundation in the field.
- Advanced coding proficiency in Python, with the ability to design, test, and correct complex scripts.
- Proficiency in SQL, for managing and manipulating data.
- Working in an Agile manner and leading Agile teams using Jira.
Some other highly valued skills include:
- Excellent modelling skills, as evidenced by an advanced degree or significant experience.
- Strong quantitative and statistical skills, enabling logical and methodical problem-solving.
- Good understanding and experience of big data technologies and the underlying approach.
- Good interpersonal skills for maintaining relationships with multiple business areas, including senior leadership and compliance.
- Ability to manage laterally and upwards across multiple discipline technical areas.
- Version control using Bitbucket, Gitlab, etc.
- Cloud experience (AWS, Azure or GCP)
You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.
This role is based in Pune.
Purpose of the role
To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.
Accountabilities
- Identification, collection, extraction of data from various sources, including internal and external sources.
- Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
- Development and maintenance of efficient data pipelines for automated data acquisition and processing.
- Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
- Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
- Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.