Skills/Requirements:

AWS

Azure

Machine Learning

Data Science

NLP

Machine Learning

Artificial Intelligence

Deep Learning

GenAI

AWS

SQL

Azure

Spark

Job Description:

Role Description

As a Senior Data Scientist specializing in Machine Learning and Deep Learning at Golden Eagle IT, you will play a crucial role in driving data-driven decisions and developing advanced analytical solutions. Leveraging your expertise in statistical analysis, predictive modeling, and artificial intelligence, you will collaborate with cross-functional teams to extract insights from complex data sets and develop scalable machine learning algorithms. The ideal candidate will have 2 to 5 years of experience in data science, with a strong background in machine learning, deep learning, and AI.

Responsibilities:

• Conduct end-to-end data analysis and develop predictive models using advanced machine learning techniques.
• Collaborate with stakeholders to understand business requirements and translate them into analytical solutions.
• Design and implement scalable algorithms for data preprocessing, feature engineering, and model training.
• Explore and evaluate emerging technologies and methodologies in machine learning and deep learning.
• Work closely with engineers to deploy models into production and monitor their performance.
• Conduct thorough testing and validation to ensure the robustness and reliability of developed models.
• Communicate findings and insights to technical and non-technical stakeholders through clear and concise presentations and reports.
• Mentor junior members of the team and contribute to the overall growth and development of the data science practice.

Requirements:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• 2 to 5 years of hands-on experience in data science, with a focus on machine learning and deep learning.
• Proficiency in programming languages such as Python, R, or Scala, along with experience in using libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of statistical techniques and experimental design.
• Experience working with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).
• Excellent problem-solving skills and the ability to work effectively in a fast-paced environment.
• Solid communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
• Demonstrated track record of delivering impactful data science solutions in a business setting.
• Experience with natural language processing (NLP) and computer vision is a plus.