Senior Data Scientist

Location:

Texas City, TX (Hybrid - 3 days a week) Duration:
Full Time / Direct Hire Looking for USC and GC Visa holders with 12 Years of Experience Final round of interview is In Person Mandatory Skills

• Data Science
• Deep Learning
• Machine Learning
• Agentic AI
• Retrieval Augmented Generation
• Large Language Model

• Data Analysis
• Machine Learning Algorithms
• Deep Learning Frameworks
• Lang chain
• AWS Bedrock
• AWS

• Develop and implement machine learning algorithms to solve complex business problems.
• Analyze large datasets to generate insights and inform decision‑making processes.
• Collaborate with product managers and engineers to integrate data science solutions into enterprise products.
• Communicate findings and recommendations effectively to technical and non-technical stakeholders.
• Stay current with the latest advancements in data science and machine learning technologies.

• Strong proficiency in programming languages such as Python or R.
• Experience with machine learning frameworks (e.g., Tensor Flow, PyTorch, Scikit‑learn).
• Solid understanding of statistical analysis techniques and data modeling.
• Proficiency in data visualization tools (e.g., Tableau, Power BI).
• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Ability to work with databases and query large datasets using SQL.
• Strong problem‑solving skills and the ability to think critically.
• Excellent communication and collaboration skills.

• A master's or Ph.D. in computer science, statistics, mathematics, or a related field.
• Experience in the tech industry or with enterprise‑level software products.
• Understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud).

• Developing and deploying machine learning models to solve business problems.
• Analyzing complex datasets to extract actionable insights that contribute to product development.
• Collaborating with cross‑functional teams to integrate data science solutions into existing products and services.
• Providing mentorship and guidance to junior data scientists and fostering a collaborative environment.

• Strong experience in machine learning algorithms and statistical modeling techniques.
• Proficiency in programming languages such as Python or R, along with data manipulation libraries.
• Experience with big data technologies like Hadoop, Spark, or similar platforms.
• Excellent analytical skills with the ability to communicate complex findings to non‑technical stakeholders.
• A degree in a quantitative field, such as Computer Science, Statistics, Mathematics, or related disciplines.