We are actively seeking a talented and experienced Data Scientist to join our dynamic team. The ideal candidate will have a strong foundation in data science, computer vision, statistical analysis, and object detection, with a focus on developing impactful solutions for complex business problems.
Responsibilities:
1. Data Analysis and Modeling:
○ Utilize advanced statistical methods and deep learning/machine learning techniques to analyse large datasets and extract valuable insights.
○ Develop predictive models and algorithms to support business decision making.
2. Domain Expertise:
○ Demonstrate expertise in the Biometrics domain or similar industry, understanding the nuances of data and business requirements.
○ Apply data science techniques to address specific challenges within the domain.
3. Feature Engineering and Data Preprocessing:
○ Conduct effective feature engineering and data preprocessing to ensure high quality input for machine learning models
○ Good Knowledge of object detection and computer vision is required.
○ Work with real-world data to derive meaningful features for analysis.
4. Coding Proficiency:
○ Exhibit strong programming skills in languages such as Python, R, or similar.
○ Should have working knowledge of developing REST API’s and frameworks like Flask/FastAPI.
○ Implement and deploy machine learning models, and contribute to codebase maintenance.
○ Must have knowledge of deep learning model training, evaluation and understanding of model inferencing.
5. Collaboration:
○ Collaborate with cross-functional teams to define data requirements and deliver solutions that meet business objectives.
○ Communicate findings and insights to both technical and non-technical stakeholders.
6. Model Evaluation and Optimization:
○ Evaluate model performance using appropriate metrics and iterate models for continuous improvement.
○ Optimise/quantize models for scalability and efficiency in real-world applications eg. edge devices.
7. Cloud and Big Data Technologies:
○ Familiarity with cloud platforms (AWS, Azure, Google Cloud) and big data technologies for efficient data processing and analysis.
8. Version Control:
a. Utilize version control systems (e.g., Git/Gitlab) to manage and track changesin code and models.
Qualifications:
● Bachelors/Master’s or Ph.D. in a relevant quantitative field such as Computer Science, Statistics, or Data Science.
● Overall 3+ years of industry work experience in computer vision, object detection, pattern recognition, artificial intelligence, automation, and/or vision processing.
● 3+ years of relevant experience as a CV Engineer, Data Scientist, Machine Learning Engineer, or related role. ● Experience with common languages (e.g., Python, SQL) and tools (e.g., TensorFlow, PyTorch, distributed training / inference) on premise or cloud.
● Knowledge of CUDA, OpenCV, Model Training on multiple GPUs.
● Proficient in at least one of: PyTorch (Preferable), TensorFlow and Keras
● Coding experience in programming Languages: Python (must), C++
● Knowledge of text detection & OCR, human / face detection, generative models, video analytics, model compression / optimization.
● Very good understanding and knowledge of Statistical and ML/DL
Concepts:
○ Statistics
○ Computer Vision
○ Regression/ Classification and Unsupervised Approaches
○ Model Training, Deployment and Evaluation
○ Ensemble approaches
○ Evaluation techniques
● Familiarity with various operating systems (e.g. Windows, UNIX) and databases (e.g. MySQL,NoSQL)
● Good team player and excellent written and verbal technical communication skills
● Experience with cloud platforms(AWS,GCP,Azure) and big data technologies is a plus.
● Experience with Docker, Kubernetes, Airflow/MLFlow is good to have