Requirements:
- A minimum of 1 to 3 years of hands-on experience in applying machine learning, data mining, and statistical analysis techniques, with a proven track record of delivering measurable commercial impact.
- Demonstrated ability to tackle high-level, loosely defined business problems and translate them into precise, quantifiable solutions.
- Strong proficiency in Python and experience with data science libraries such as Pandas, NumPy, and Scikit-learn.
- Experience with version control systems like Git and containerization tools like Docker.
- Self-motivated and resourceful individual capable of exploring various tools and crafting code and scripts for data manipulation, experimentation, algorithm implementation, and accuracy assessments.
- Proficient in databases and engines for both structured and unstructured data, data transformation (ETL), distributed computing, software development methodologies, and data science languages such as PySpark and SQL.
- Excellent communication skills, with the ability to articulate complex data insights clearly and effectively to both internal stakeholders and external clients
Preferred Qualifications:
- Experience or background in working with Large Language Models (LLMs) or related natural language processing (NLP) techniques.
- Proficiency in Computer Vision (CV) techniques or related skill sets.
- Familiarity with advanced topics in AI and machine learning, such as deep learning, reinforcement learning, or NLP.