Data Scientist (Remote)
Our client is looking for a
Data Scientist
to support the development and implementation of advanced data and AI strategies. The ideal professional is passionate about data-driven innovation and eager to work with cutting-edge technologies in Machine Learning and Generative AI.
Key Responsibilities
Develop and implement data strategies to support business objectives and innovation.
Collaborate with business and technology teams to identify opportunities for data-driven improvements.
Design, train, and validate
Generative AI
and
Machine Learning
models.
Monitor and optimize
NLP
and
Generative AI
model performance to ensure accuracy and relevance.
Evaluate and fine-tune pre-trained models to address specific business challenges.
Ensure data privacy, security, and bias mitigation in AI models.
Build prediction and recommendation models, providing actionable insights.
Collaborate with data engineers to design efficient data pipelines.
Maintain data inventories and dictionaries, ensuring data quality and consistency.
Drive innovation by proposing improvements and new business solutions using Generative AI.
Stay current with advances in AI, NLP, and emerging frameworks.
Promote a
data-driven culture
within cross-functional teams.
Requirements
Bachelor's degree in a technology-related field.
Solid experience with
Machine Learning algorithms
, from design to deployment and automation.
Proven background developing Data Science solutions: optimization, classification, prediction, statistical analysis, and NLP.
Hands-on experience with
LLMs
,
RAG
, and
Generative AI
(e.G., Amazon Bedrock).
Strong proficiency in
Python
,
statistics
, and
AI/ML frameworks
.
Advanced knowledge of
relational
(SQL Server, PostgreSQL) and
non-relational databases
.
Experience with
Databricks
(Spark optimization, Delta Lake, MLflow).
Familiarity with
AWS
services such as S3, Athena, Glue, SageMaker, and QuickSight.
Experience implementing
MLOps
best practices.
Advanced English
(verbal and written).
Nice to Have
Expertise in
Big Data
and advanced use of
Databricks
to accelerate AI and analytics initiatives.
Research or projects published in
NLP
or
Generative AI
fields.