Data Scienist

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