Senior Data Scientist

Job Description:

Responsibilities:
● Develop and refine machine learning models, including NLP,
classification, decision trees, and XGBoost, to enhance business
decision-making processes.
● Design and deploy generative AI models, LLMs, SLMs, and chatbots
to automate and optimize customer interactions and internal
workflows.
● Implement advanced data retrieval and analysis techniques, such as
RAG, clustering, summarization, prediction, and keyword/topic
extraction.

● Build and maintain robust knowledge bases and utilize trend
detection, sentiment analysis, anomaly detection, and PII redaction to
ensure data integrity and relevance.
● Engineer scalable data pipelines and architectures, manage data
lakes, and perform ETL processes to support data science initiatives.
● Optimize data storage and retrieval in AWS environments, using
specific services such as Amazon SageMaker, Amazon Redshift,
Amazon OpenSearch, and AWS Bedrock.
● Lead data strategy sessions and communicate findings and
strategies effectively to stakeholders at all levels.

Requirements:
● Proven experience in data science with a strong portfolio of projects
demonstrating expertise in machine learning, NLP, generative AI, and
other listed technologies.
● Proficient in data engineering tasks, including data cleaning, schema
design, and the development of scalable ETL processes.
● Solid experience with AWS cloud services, particularly Amazon
SageMaker, Amazon Redshift, Amazon OpenSearch, and AWS
Bedrock; familiarity with Azure or Google Cloud is a plus.
● Excellent communication and team collaboration skills.
● Ability to design complex data science architectures and directly
implement solutions with a high level of autonomy.

Qualifications:
● Master’s degree in Data Science, Computer Science, Statistics, or a
related field.
● Minimum of 5 years of experience in a data science role.
● Strong programming skills in Python, R, SQL, and familiarity with API
integrations.