Data Scientist

Job Description

Job Description

We are looking for an experienced Data Scientist to join our team in San Antonio, Texas. In this role, you will design and implement advanced machine learning models, analyze complex datasets, and deliver actionable insights to support data-driven decision-making. The ideal candidate will have a strong technical background and a passion for leveraging data science to solve real-world challenges.

Responsibilities:
• Develop and deploy machine learning models, including supervised and unsupervised learning techniques, to address business challenges.
• Apply deep learning frameworks such as TensorFlow and PyTorch to build and optimize AI-driven solutions.
• Conduct statistical analyses and data visualizations to uncover trends and deliver meaningful insights.
• Collaborate with cross-functional teams to understand requirements and translate business needs into data-driven strategies.
• Utilize data mining techniques to identify patterns, relationships, and opportunities within large datasets.
• Implement natural language processing (NLP) methods to analyze and interpret unstructured text data.
• Maintain and enhance ETL processes to ensure data quality and accessibility for analytical purposes.
• Design dashboards and reports that effectively communicate findings and support strategic decision-making.
• Uphold ethical standards in data usage, ensuring responsible innovation and mitigating biases.
• Stay updated on industry trends and emerging technologies to continuously improve data science practices.• Bachelor’s degree in Information Technology or a related field; Master’s or Ph.D. in Computer Science, Statistics, or Mathematics is preferred.
• Minimum of 5 years of experience in data science or a related field with a strong attention to detail.
• Proficiency in programming languages such as Python and expertise in machine learning frameworks like TensorFlow, PyTorch, and scikit-learn.
• Strong understanding of machine learning algorithms, including deep learning techniques.
• Experience with big data tools such as Apache Spark, Hadoop, and Kafka.
• Knowledge of ETL processes and data clustering methodologies.
• Familiarity with natural language processing tools, including Natural Language Toolkit (NLTK).
• Excellent analytical and problem-solving skills with the ability to work independently and collaboratively.