- The Data & Analytics team is responsible for integrating new data sources, creating data models,
- developing data dictionaries, and building machine learning models for Wholesale Bank. The
- primary objective is to design and deliver data products that assist squads at Wholesale Bank in
- achieving business outcomes and generating valuable business insights. Within this job family,
- we distinguish between Data Analysts and Data Scientists. Both roles work with data, write
- queries, collaborate with engineering teams to source relevant data, perform data munging
- (transforming data into a format suitable for analysis and interpretation), and extract meaningful
- insights from the data. Data Analysts typically work with relatively simple, structured SQL
- databases or other BI tools and packages. On the other hand, Data Scientists are expected to
- develop statistical models and be hands-on with machine learning and advanced programming,
- including Generative A Requirements
- We are seeking a highly skilled Data Science and Generative AI Specialist with 2+ years of
- experience in machine learning, deep learning, or AI research, with a focus on generative models.
- The ideal candidate will have strong expertise in data science, machine learning, and generative
- AI, with specific experience in document detail extraction, feature engineering, data processing
- using Python, and familiarity with tools such as Streamlit for data app creation. The candidate
- must also possess advanced skills in prompt engineering, chain of thought techniques, and AI
- agents to drive our cutting edge projects forward Key Responsibilities:
- Develop and implement machine learning models for document detail extraction and
- data processing.
- Perform feature engineering to enhance predictive models and data algorithms.
- Implement advanced data augmentation, feature extraction, and data transformation
- techniques to optimize the training process.
- Deploy generative AI models into production environments, ensuring they are scalable,
- efficient, and reliable for real time applications.
- Use cloud platforms (AWS, GCP, Azure) and containerization tools e.g., Docker,
- Kubernetes) for model deployment and scaling.
- Utilize Python and libraries such as pandas, NumPy, scikit learn, TensorFlow, and PyTorch
- for data analysis, processing, and model development.
- Create interactive data applications using Streamlit for various stakeholders. Qualifications:
- 2+ years of experience in machine learning, deep learning, or AI research, with a focus on
- generative models.
- Experience with generative models such as GANs (Generative Adversarial Networks),
- VAEs Variational Autoencoders), and transformer based models
- Understanding of model fine tuning, transfer learning, and prompt engineering in the
- context of large language models (LLMs).
- Knowledge of reinforcement learning (RL) and other advanced machine learning
- techniques applied to generative tasks. Strong programming skills in Python and familiarity with relevant libraries and
- frameworks.
-
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gen ai - Hyderabad / Secunderabad, Telangana - Virtusa
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