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Engaged Employer

TechVantage Systems

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2.9

based on 19 Reviews

2 TechVantage Systems Senior Data Scientist Jobs

Senior Data Scientist

TechVantage Systems Private Limited

2.9

based on 19 Reviews

3-8 years

Thiruvananthapuram

1 vacancy

Senior Data Scientist

TechVantage Systems

posted 1mon ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analysis Data Analytics Machine Learning Project Management Analytical Chemistry Natural Language Processing

+ 4 more

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 Senior Data Scientist with expertise in Generative AI to join our dynamic team and drive advancements in our data-driven initiatives.

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.

What we are looking from an ideal candidate

Position Overview

As a Senior Data Scientist, you will play a pivotal role in developing and deploying state-of-the-art AI solutions. 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.

Identification of Use cases

Participate in discussions with end clients and identify potential opportunities to apply AI to optimize business and spot the right use cases for applied AI.

Model building and algorithm selection

Problem understanding, Data collection, EDA, Algorithm selection, Model building and hyperparameter tuning, Evaluation, deployment and monitoring of models

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 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 models seamlessly into existing systems and workflows.

Preferred Skills: What skills do you need

3+ 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.

Strong understanding of parameters influencing the performance of machine learning models and the ability to optimize these models for better outcomes.

Strong background in Natural Language Processing, including experience with text representation, language modeling, sequence-to-sequence architectures, and semantic understanding.

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

Experience with LangChain, LLAMAIndex, Foundation model tuning, Data Augmentation, and Performance Evaluation frameworks

Expertise in Design, development, and optimization of high-quality prompts and templates that guide the behaviour and responses of LLM will be essential.

The ideal candidate will have the ability to interact with Chief Data Officers, Chief Marketing Officers, Chief Risk Officers, Chief Technology Officers, and Chief Information Officers, as well as the people within their organizations.