Location
Trivandrum | India
Job description
Techvantage Analytics is a fast-growing AI services and Product Engineering company specialized in Analytics, Machine learning and AI-based solutions. We are looking for a skilled and passionate Lead Data Scientist with expertise in Generative AI to join our dynamic team.
To succeed in this position; you need to be curious, creative, and tech-savvy. Keeping abreast of advancements in data programming, showcasing a deep grasp of statistics and mathematics, and displaying prowess in algorithmic writing are key. Ideal candidates will exhibit persistence alongside exceptional analytical and problem-solving abilities.
Position Overview
As a Senior Data Scientist, you will play a pivotal role in developing and deploying state-of-the-art generative models. You will collaborate closely with cross-functional teams to explore, experiment, and apply Generative AI techniques to solve complex business challenges and create innovative solutions.
Roles and Responsibilities:
Generative Model Development:
- Design, develop, and implement cutting-edge generative AI models, such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs), to create synthetic data or generate realistic outputs.
- Explore and experiment with various architectures and techniques to optimize generative model performance.
Data Analysis and Preprocessing:
- Conduct thorough exploratory data analysis (EDA) to gain insights into the underlying data distribution.
- Implement data preprocessing techniques to clean, normalize, and augment datasets for generative model training.
Model Training and Evaluation:
- Develop and execute training pipelines for generative models, considering factors such as hyperparameter tuning and regularization.
- Evaluate model performance using appropriate metrics, adjusting models as needed to improve quality and efficiency.
Cross-functional Collaboration:
- Collaborate with cross-functional teams, including data engineers, domain experts, and business stakeholders, to understand requirements and align generative AI solutions with business objectives.
- Communicate effectively to non-technical stakeholders regarding model outcomes and potential applications.
Research and Innovation:
- Stay current with the latest research in generative AI and related fields.
- Propose and implement innovative approaches to enhance generative model capabilities and applications within the organization.
Ethical Considerations:
- Implement ethical considerations in generative AI model development, ensuring fairness, transparency, and compliance with relevant regulations.
- Address and mitigate potential biases in generated outputs.
Documentation and Reporting:
- Document the end-to-end development process, including data preprocessing steps, model architectures, training methodologies, and evaluation results.
- Prepare clear and concise reports, making findings accessible to both technical and non-technical audiences.
Continuous Learning and Skill Development:
- Pursue continuous learning opportunities to stay abreast of advancements in generative AI, attending conferences, workshops, and online courses.
- Actively participate in skill-building activities within the organization.
Project Management:
- Manage the full lifecycle of generative AI projects, from scoping and planning to execution and delivery, ensuring projects align with organizational goals and timelines.
Deployment and Integration:
- Collaborate with IT and software development teams to deploy generative AI models into production environments.
- Integrate generative models seamlessly into existing systems and workflows.
Skill Sets and Qualifications
- Minimum of 4+ years of experience as a Data Scientist.
- Proficient in machine learning and statistical modeling techniques, with a demonstrated track record of applying these methods effectively for data analysis and problem-solving for at least 4+ years.
- Strong understanding of parameters influencing the performance of machine learning models and the ability to optimize these models for better outcomes.
- Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science.
- Proven experience in researching and applying large language and generative AI models is mandatory.
- Hands-on experience in developing models, in optimizing model training and tuning and in deploying LLMs such as GPT, LLaMA, Falcon, BERT, or Transformer-based architectures
- Strong background in Natural Language Processing, including experience with text representation, language modeling, sequence-to-sequence architectures, and semantic understanding
- 3+ years of experience of technical architecture, design, deployment and operational level knowledge
- Large models pretrain/fine-tuning experience, familiar with distributed training
- Design, develop, and optimize high-quality prompts and templates that guide the behaviour and responses of LLM. Craft prompts to elicit specific information or control the model's output, ensuring desired accuracy, relevance, and language fluency.
- Experience with LangChain, LLAMAIndex, Foundation model tuning, Data Augmentation, and Performance Evaluation frameworks
- Should be able to interact with Chief Data Science Officers, Chief Marketing Officers, Chief Risk Officers, Chief Technology Officers, and Chief Information Officers, as well as the people within their organizations.
- Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment.
- Track record of thought leadership and innovation around Machine Learning.
- Effective and articulate communication abilities are essential attributes sought for this position.
- Furthermore, a positive and proactive attitude toward problem-solving and teamwork is highly valued and recommended for this role.
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