Data Scientist

1 Data Scientist

Establishing a single, end-to-end synaptic-based model (for evaluation) and being prepared to hook it up for model deployment for online testing

The resource will come in having experience in modeling work at a production level, this resource will not be doing any research-related type of work. System understanding + modeling
deliverables are key stills for this role. This person should have a sense of things they build in preparation for production and be able to articulate that

Dive into the data to understand its structure, volume, and any existing preprocessing. This may involve:
Data Cleaning: Handling missing values, removing duplicates, and standardizing formats.
Exploratory Data Analysis (EDA): Analyzing patterns and distributions, assessing feature relevance, and identifying potential biases.
Familiarity with data nuances and readiness to create initial embeddings.
Generate embeddings, likely using pre-trained or fine-tuned language models, for candidate retrieval data. Embeddings for retrieval and have evaluation results, evaluating results of the model and have that artifact ready for deployment understanding the data, and build indexes

MUST HAVE:
SQL- programming language - proficient
Java code - required
Python - expert
Code versioning software (Git)
Machine learning:
Deep learning (including large language models and/or computer vision)
Data pipeline engineering
Model deployment /development (write a model from scratch, infrastructure pipelining)

Nice to have:
Some experience in search (Lucene)
Some experience with Synaptic-based Language Modeling and Vector Databases (VectorDB)