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:

â—‹ 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.

â—‹ 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.

â—‹ Work with real-world data to derive meaningful features for analysis.

4. Coding Proficiency:

â—‹ 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.

â—‹ Communicate findings and insights to both technical and non-technical stakeholders.

6. Model Evaluation and Optimization:

â—‹ 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:

â—‹ Statistics

â—‹ 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