Senior Data Scientist (Computer Vision)

About Us:

DIGITAP.AI is a cutting-edge provider of AI/ML solutions tailored for the modern, internet-driven business landscape. Our advanced technologies empower businesses with reliable, fast, and fully compliant customer onboarding, automated risk management, and big data-enabled services, including Risk Analytics and Customised Scorecards.

Our proprietary machine learning algorithms and modules boast some of the highest success rates in the market. Partnering with the largest digital lenders in India, our team is a vibrant mix of expertise in Fintech Product & Risk Management, Fraud Detection, and Big Data Analytics.

Culture and Benefits:

• Innovative Start-up Environment: Enjoy the flexibility to design, implement, and influence the development of cutting-edge solutions.
• Transparency and Meritocracy: We value clear communication, eschew politics, and promote an open culture where contributions are recognized and rewarded.
• Ownership and Impact: We encourage team members to take ownership, think beyond their roles, and contribute to the company's success in meaningful ways.
• Competitive Compensation: We offer a competitive salary and a potential equity package, aligning your success with the company's growth.
  
  
  

Job Description:

As a Senior Data Scientist specialising in Computer Vision, you will lead projects that leverage deep learning and computer vision techniques to solve complex challenges in the fintech and risk management domains.

Key Responsibilities:

• Lead Computer Vision Initiatives: Develop and deploy advanced computer vision models for tasks such as object detection, image classification, data extraction, and image quality assessment.
• Drive Innovation in Core-ML Projects: Work on critical machine learning projects, including Credit Risk Modeling and Scorecard Development, ensuring robust and scalable solutions.
• Data Exploration and Analysis: Explore and analyse unstructured data, particularly images, using advanced image processing techniques.
• Model Research and Development: Collaborate with the data science team to research, develop, evaluate, and optimise deep learning models tailored to solve specific business problems.
• Product Integration and Enhancement: Work closely with engineering and product teams to integrate models into production, deploy solutions, and continuously improve the product based on customer feedback.
• Enhance Data Collection: Design and implement data collection strategies to capture critical information, enhancing the accuracy and reliability of analytic systems.
• Transform Research into Action: Translate cutting-edge research articles and methodologies into practical solutions to address real-world challenges.
  
  
  

Required Skills and Experience:

• Deep Learning Expertise: 3+ years of hands-on experience in Computer Vision and deep learning, particularly in object detection and image classification.
• Proficiency with ML Frameworks: Strong experience with machine learning frameworks such as PyTorch, TensorFlow, and Keras.
• GPU Computing: Proven experience in training models using GPU computing (e.g., NVIDIA CUDA) or cloud-based environments.
• Python Proficiency: Strong programming skills in Python and familiarity with relevant libraries, including NumPy, scikit-image, PIL, OpenCV, matplotlib, and seaborn.
• Database and API Expertise: Solid experience with SQL databases and API integration.
• Cloud Computing: Proficiency in deploying and managing models in cloud environments like AWS.
• Problem-Solving Mindset: Ability to independently tackle complex problems and implement innovative solutions.
  
  
  

Preferred Qualifications:

• Qualification: BE, BTech, MTech, ME, MCA (minimum 4 years of degree)
• Experience: 3-5 Years
• Leadership Experience: Prior experience leading projects or teams in data science or computer vision.
• Industry Experience: Familiarity with the fintech or risk management industry.
• Continuous Learning: A strong desire to stay updated with the latest research and advancements in AI, ML, and computer vision.