Data Scientist for Biometrics Advancements
20 hours ago
Unlocking Business Potential through Data Science at Biocube
Become a part of our dynamic team at Biocube and take on the challenge of shaping the future of data science. We are looking for an exceptional Data Scientist who can leverage their expertise in data analysis, modeling, and machine learning to drive business growth.
Key Responsibilities:- Data Analysis and Modeling Strategies:
- Employ advanced statistical methods and machine learning techniques to unlock hidden patterns in large datasets.
- Design and implement predictive models to inform strategic business decisions.
- Domain Expertise in Biometrics:
- Demonstrate comprehensive knowledge of the Biometrics domain and its intricacies.
- Apply data science techniques to address complex challenges within the domain.
- Feature Engineering and Data Preprocessing Best Practices:
- Develop effective feature engineering strategies to ensure high-quality data input for machine learning models.
- Strong understanding of object detection and computer vision principles.
- Extract meaningful features from real-world data to drive business insights.
- Coding Expertise in Python and Similar:
- Demonstrate proficiency in programming languages such as Python, R, or similar.
- Excellent understanding of developing REST APIs and frameworks like Flask/FastAPI.
- Implement and deploy machine learning models while maintaining code quality.
- Collaboration and Communication:
- Collaborate with cross-functional teams to identify data requirements and deliver impactful solutions.
- Effectively communicate findings and insights to both technical and non-technical stakeholders.
- Model Evaluation and Optimization Techniques:
- Evaluate model performance using relevant metrics and refine models for continuous improvement.
- Optimize models for scalability and efficiency in real-world applications.
- Cloud and Big Data Technologies Familiarity:
- Familiarity with cloud platforms (AWS, Azure, Google Cloud) and big data technologies for efficient data processing and analysis.
- Version Control Systems:
- Utilize version control systems (e.g., Git/Gitlab) to manage and track changes in code and models.
- Bachelor's/Master's or Ph.D. in a relevant quantitative field such as Computer Science, Statistics, or Data Science.
- Minimum 3+ years of industry experience in computer vision, object detection, pattern recognition, artificial intelligence, automation, and/or vision processing.
- 2+ years of relevant experience as a CV Engineer, Data Scientist, Machine Learning Engineer, or related role.
- Proficient in common languages (e.g., Python, SQL) and tools (e.g., TensorFlow, PyTorch, distributed training/inference).
- Knowledge of CUDA, OpenCV, Model Training on multiple GPUs.
- Proficient in at least one of: PyTorch (Preferred), TensorFlow, and Keras.
- Coding experience in programming Languages: Python (required), C++.
- Knowledge of text detection & OCR, human/face detection, generative models, video analytics, model compression/optimization.
- Excellent 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.
Salary: $120,000 - $180,000 per year
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