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)
- Positive 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

📌 Data Scienist (Noida)
🏢 Bioqube Technologies
📍 Noida