Data science engineer

Responsibilities:

Lead the data science field within the company.

Build & Refine the company's AI / ML algorithms.

Proactively seek new directions for tackling hard-to-crack problems, including devising real-world experiments and data collection.
Develop and implement advanced algorithms and models to process unstructured documents like PDFs, extracting insights through entity recognition.

Collaborate cross-functionally to translate business needs into actionable data science solutions, conducting thorough data analysis and feature engineering to uncover trends within unstructured data.

Working closely with the company's CTO and architect.

Requirements

Technical Skills:

3+ years of experience in data science
1 year of experience in Natural Language Processing (NLP) research or related fields.
Strong knowledge of machine learning and AI, particularly in building and deploying predictive modeling solutions.
AI / ML experience with Big Data.
Deep understanding of both theory and practice of ML.
Proficient in various data store technologies (SQL/ NoSQL).
Strong expertise in Python
Experience with Deep Learning architectures - CNN, RNN, LSTM, Transformer, etc.
Experience with TensorFlow, PyTorch, sci-kit learn, etc.
Experience with Hierarchical Multimodal Classifier.
Experience with transfer learning.
Experience with AWS infrastructure.

Personal Traits:

Motivated and eager to tackle challenges with a “can-do attitude”.
Proven track record of excellence in solving machine learning challenges.
Communication skills & ability to articulate complex topics.
Ability to deliver A-Z projects.
Can-do attitude willing to tackle big challenges.
Team player who wants to be part of something greater.
Desire to learn new things and create.