We are looking for Lead Data scientists who can utilize their analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. They then use this information to develop data-driven solutions to difficult business challenges. Looking for candidates with a wide range of technical competencies including: statistics and machine learning, coding languages, databases, machine learning, and reporting technologies. As a Data Science Lead, you will be responsible for building and managing a team of data scientists and analysts, developing and implementing data-driven solutions, and ensuring the accuracy and reliability of our data and insights.
- Manage a team of data scientists and analysts to develop and implement data-driven solutions that improve customer engagement, loyalty, and satisfaction
- Collaborate with cross-functional teams including product management, engineering, and design to define and prioritize data science projects
- Communicate findings and recommendations to stakeholders and senior management in clear and concise manner
- Stay up-to-date with the latest data science techniques, tools, and technologies, and apply them to solve complex business problems
- Provide technical leadership and mentorship to the data science team
- Analyze raw data: assessing quality, cleansing, structuring for downstream processing
- Design accurate and scalable prediction algorithms
- 2-5 years of demonstrated experience as a machine learning engineer/data scientist
- Minimum 2-year experience in working with NLP/NLU projects.
- Understanding of data pipelines for machine learning & deep learning.
- Hands on experience on ML Ops, Sagemaker and Auto ML.
- Hands on experience on Hugging face models, transformers etc.
- Experience in working with generative models like GPT-3, chatgpt etc.
- Hands-on experience on Prompt design for chat gpt.
- Hands on experience on development and deployment using flask/ fast api, docker.
- knowledge of multilabel and multiclass text classification.
- Hands-on experience with the industry-standard models like BERT, Yolo … etc
- Proficiency with core python programming (minimum 3 years). Heterogeneous programming experience.
- Proficiency with Algorithms and Data Structures.
- Experience with Git and version control best practices
- Programming experience with deep learning frameworks such as TensorFlow or PyTorch.
- Experience in building and deploying computer vision and NLP solutions at scale.
- Hands-on experience in working with ML problems (ex, Classification/Regression/Anomaly Detection)
- Understanding of REST concepts, Ability to consume third-party libraries and APIs
- Experience in Data Scraping and selenium automation.
- Deep understanding of Concepts like Probabilistic Reasoning & Statistical Inference, Cost Functions, etc.
- Good understanding of both structured and unstructured databases, for example, SQL, MongoDB, etc.
- Bachelor’s degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 1 – 2 years’ of experience in quantitative analytics or data modeling
- Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
- Fluency in a programming language (Python)