SP Software - Team Lead - Data Science (6-9 yrs)

Job Position :

We are looking for a Team Lead with experience in people management and good hands-on knowledge on AI/ML/DL/NLP/LLM model development.

Job Responsibility

Interface with business/operation teams and key stakeholders at all levels to formulate solutions &

suggest them actionable insights with clear business benefit of proposed solution.

Manage the continuous improvement of data science and machine learning led initiatives by following

industry best practices and staying up to date with and extending the state-of-the-art in data science

research.

Provide technical leadership for a team of data scientists to deliver machine learning solutions.

Manages and leads team, communicates goals and objectives, provides iterative feedback and monitors

performance of team members.

Contributes to the growth of the organization in hiring, training, and mentoring teams.

QUALIFICATION

B.E/B.Tech in Computer Sciences, IT, Engineering or Masters in Data Science /AI ML fields

EXPERIENCE

- Min 8+ years of overall SDLC / IT experience.

- 2+ years of people management experience

- At least 3 years of experience in Agile implementation.

- Minimum of 3 years of experience working with large data sets or do large scale quantitative analysis

- 2+ years of experience in implementing machine learning models: Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms.

- Solid experience working with LLMs, such as GPT3/ Llama/ T5/ BERT, and NLP frameworks, like Hugging Face Transformers, PyTorch /JAX

SKILLS AND COMPETENCIES :

- At least 2 years of experience in leading high performing team, sized at 8-10 members, in delivering AI

based solutions.

- At least 3 years of experience in Agile implementation.

- Minimum of 3 years of experience working with large data sets or do large scale quantitative analysis

- Authoritative experience in the field of Data Science to influence stake holders across varied work

streams and geographical locations, ability to challenge the status quo to improve the base line models

and the models which are already productionized.

- Experience in implementing machine learning models: Forecasting, Classification, Data/Text Mining,

NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural

Networks, Deep Learning Algorithms.

- Strong implementation experience with Python, and familiarity with Linux/Unix/Shell environments

- Hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data using

distributed computing platform.

- Familiarity of data architecture requirements and conceptual approaches for deploying algorithmic

solutions in Big Data productive environments.

- Worked with at least one mainstream machine learning frameworks, including caffe, convNet, Tensor

Flow, Torch

- Working proficiency with SQL and relational databases, data warehouse

- Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments.