Position Overview:
As a Senior Data Scientist, you will play a crucial role in driving our data-driven
initiatives for our customers, contributing to the development and implementation of advanced deep
learning models and algorithms. Your expertise will be instrumental in extracting valuable insights from
vast and diverse datasets, enabling data-driven decision-making and delivering solutions that positively
impact our customers and business.
Responsibilities:
- Research and Development: Lead the research, design, and implementation of state-of-the-art
deep learning algorithms to tackle complex business problems and enhance data-driven
solutions. Familiarity with Fraud Detection models is nice to have. - Model Development: Build and optimize robust deep learning models using Python and various
deep learning frameworks (e.g., TensorFlow, PyTorch, Keras) for various applications, such as
natural language processing, computer vision, and recommender systems. - Data Preprocessing: Oversee data preprocessing and cleaning pipelines to ensure data quality
and relevance for training deep learning models, working closely with data engineers and other
stakeholders. - Evaluation and Optimization: Conduct rigorous performance evaluations of deep learning models, fine-tune hyperparameters, and optimize models to achieve superior accuracy and
efficiency. - Collaborative Projects: Collaborate with cross-functional teams including data scientists,
engineers, and domain experts to integrate deep learning solutions into our products and
services. - Emerging Technologies: Stay up-to-date with the latest advancements in deep learning, machine learning, and artificial intelligence, and proactively recommend and apply innovative
techniques to improve existing solutions. - Communication: Clearly communicate complex technical concepts, methodologies, and findings
to both technical and non-technical stakeholders through presentations, reports, and
visualizations. - Mentorship: Provide mentorship and guidance to junior data scientists, fostering a culture of
continuous learning and professional growth within the team.
Qualifications:
- Master’s or Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.
- Minimum of 5+ years of professional experience as a Data Scientist, with a strong focus on deep
learning projects. - Extensive hands-on experience with Python programming and deep learning frameworks
(TensorFlow, PyTorch, Keras, etc.). - Proficiency in data preprocessing, feature engineering, and data visualization techniques.
- Proven track record of successfully developing and deploying deep learning models for real-world
applications. - Solid understanding of statistical analysis, machine learning algorithms, and their applications.
- Strong problem-solving skills, with the ability to think critically and creatively to solve complex
challenges. - Excellent communication and teamwork skills, with the ability to collaborate effectively with
cross-functional teams. - Experience with cloud platforms (e.g., AWS, Azure, GCP) and distributed computing is a plus.