- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress Utilize the existing frameworks, standards, patterns to create architectural foundation and services necessary for AI applications that scale from multi-user to enterprise class
- Managing Data Science project life cycle from exploratory data analysis to productization (Alpha/Beta Release) .Manage small team to collaborate with Architecture, Data Warehouse, Data Governance teams for providing analytics as service.
- Mentor team member for AI/ML development
- Verifying data quality, and/or ensuring it via data cleaning Supervising the data acquisition process if more data is needed Finding available datasets online that could be used for training Defining validation strategies Defining the preprocessing or feature engineering to be done on a given dataset.
- Defining data augmentation pipelines Training models and tuning their hyperparameters Analyzing the errors of the model and designing strategies to overcome them Deploying models to production.
- Development of the ML algorithms that could be used to solve a given problem and ranking them by their success probability.
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
Knowledge / Experience / Competencies Required
IT Skills Experience (Priority wise):
1. Proven experience as a Data Scientist AI/ML or similar role
2. Ability to write robust code in Python.
3. Experience in the Generative AI components like LLMs, LangChain, LlamaIndex, OpenAI, Mistral, Llama etc.
4. Experience in supervised/semi-supervised and unsupervised machine learning algorithms.
5. Experience using the cognitive APIs machine learning studios on cloud.
6. Up to speed on NLP (Summarization, Translation models, Named Entity Recognition)
7. Hands-on knowledge of image processing with deep learning (CNN, RNN, LSTM, GAN)
8. Understanding of complete AI/ML project life cycle.
9. Understanding of data structures, data modelling and software architecture.
People Skills:
- Ability to communicate clearly and concisely and a flexible mindset to handle a quickly changing culture
- Ability to work independently and/or as part of cross-domain big team
- Professional and open communication to all internal and external interfaces.
- Accurately report to management in a timely and effective manner.
Other Skills:
- Outstanding analytical and problem-solving skills
- Taking ownership of the tasks in hand and being accountable for deliverables.
Education Qualifications, Accreditation, Training:
- Minimum 4 7 years experience as a Data Scientist on AI and ML projects.
- Master s in information technology / Big Data/Data Science/AI/Computer Science or related field
