Scienaptic - Lead Data Scientist

Primary Responsibilities:

- Lead/Manage and Mentor a Team of Data Scientists, Data Analysts & Data Engineers, along with growing the Account/Team Size.

- Work as partner with Business in driving critical KPI improvements.

- Establish Scalable, Efficient Solutions for large scale Data Analysis, AI/ML Model Development, AI/ML Model Validation, AI/ML Model Implementation and AI/ML Model Automation.

- Writing Efficient, Reusable, Testable, and Scalable SQL, R & Python Code.

- Adhere to stringent Quality Assurance and Documentation Standards using Version Control and Code Repositories (e.g., Git, GitHub, Markdown).

- Communicate Complex Data or Algorithms into simple Conclusions that will empower Leadership to drive action based on the Insights derived.

- Design and implement reporting and metrics that track and monitor the performance of our Projects.

- Responsible for End-to-End Project Delivery & Stakeholder Engagement/Management.

- Oversee the Planning, Execution, and Delivery of all the Projects.

- Actively participate in Data analysis, Model development, and Evaluation.

- Collaborate with Team Members to improve the Accuracy and Performance of AI/ML Algorithms.

- Work closely with the Management Team to develop Data Science strategies that align with Business Objectives.

- Identify opportunities to leverage Data for Business Growth and Optimization.

Requirements:

- Ability to Analyse complex Data and provide recommendations to Business.

- Proficient with Statistical Analysis, AI/ML Algorithms & applying them on Large Datasets.

- Establish Scalable, Efficient Solutions for large scale Data Analysis, AI/ML Model Development, AI/ML Model Validation, AI/ML Model Implementation and AI/ML Model Automation (MLOps).

- Excellent proficiency in Core Python Fundamentals, Python Programming, and other relevant Python Frameworks (such as Django, Flask etc.), Object Relational Mapper Libraries, SQL; Experience in No SQL Database like Mongo DB.

- Strong knowledge of AI/ML/DL Techniques, Algorithms, and tools with exposure to CNN, RNN (LSTM), Transformers (BERT).

- Experience with Training BERT, LSTM for different NLP tasks.

- Exposure to NLP Data Wrangling and Tokenization.

- Proficiency in working with Open-Source Deep Learning libraries like TensorFlow, Keras, Pytorch.

- A demonstrated ability to mentor Junior Team Members and proven Experience in collaborative work environments with External Clients & Project Management.

- Proficient in communicating technical findings to Non-Technical Stakeholders.

- Strong Presentation and Communication Skills.

- Identify opportunities to grow the Account.