Position Overview:
NstarX is seeking a Junior Data Scientist to join our data-driven team. In this role, you will contribute to the development and implementation of deep learning models and algorithms, playing a key role in extracting insights from diverse datasets. This position is an excellent opportunity to apply your data science knowledge in a practical setting, enabling data-driven decision-making and delivering solutions that positively impact our customers and business.
Responsibilities:
- Support Research and Development: Assist senior data scientists in the research, design, and implementation of advanced deep learning algorithms to solve complex business problems.
- Model Development: Participate in building and optimizing deep learning models using Python and deep learning frameworks (e.g., TensorFlow, PyTorch, Keras) for applications including natural language processing, computer vision, and recommender systems.
- Data Preprocessing: Collaborate with data engineers to prepare and clean data for model training, ensuring data quality and relevance.
- Model Evaluation and Optimization: Help evaluate the performance of deep learning models, assist in fine-tuning hyperparameters, and contribute to optimizing models for better accuracy and efficiency.
- Collaborative Projects: Work closely with cross-functional teams, including data scientists, engineers, and domain experts, to integrate deep learning solutions into our products and services.
- Stay Updated: Keep abreast of the latest advancements in deep learning, machine learning, and AI, and explore innovative techniques to enhance our solutions.
- Communication: Develop and hone your ability to communicate complex technical concepts and findings to both technical and non-technical stakeholders.
- Professional Growth: Engage in opportunities for learning and professional development under the mentorship of more experienced data scientists.
Qualifications:
- Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.
- 1-2 years of professional experience in a data science role, with exposure to deep learning projects.
- Proficiency in Python programming and experience with deep learning frameworks (TensorFlow, PyTorch, Keras, etc.).
- Familiarity with data preprocessing, feature engineering, and visualization techniques.
- An understanding of statistical analysis, machine learning algorithms, and their applications.
- Strong analytical skills, with the ability to tackle complex problems creatively.
- Excellent communication skills and the ability to work effectively in a team.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and distributed computing is beneficial.