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Dexian

AI/ML Data Scientist #981755 (Seffner)

Dexian, Seffner, Florida, United States, 33583

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Job Title:

AI Data Scientist Location:

Seffner, FL Employment Type:

Contract-to-Hire

Position Overview We are seeking an experienced

AI Data Scientist

to design, develop, and implement advanced machine learning and artificial intelligence solutions leveraging

Databricks ,

Python ,

Azure , and

SQL . The ideal candidate will have strong experience building and deploying data-driven models in cloud environments, collaborating with data engineers and business stakeholders to turn complex datasets into actionable insights.

Key Responsibilities Develop, train, and deploy

machine learning and AI models

for predictive analytics, automation, and optimization use cases. Utilize

Databricks

for scalable data processing, model training, and orchestration of ML pipelines. Write efficient and reusable

Python

code for data preprocessing, feature engineering, and model development. Work within

Azure Machine Learning

and

Azure Data Factory

environments to manage model lifecycles and data workflows. Query, clean, and analyze large datasets using

SQL

to extract meaningful trends and patterns. Collaborate with

data engineers ,

analysts , and

business stakeholders

to understand objectives and deliver data-driven solutions. Evaluate model performance using appropriate metrics and continuously refine algorithms for accuracy and efficiency. Implement MLOps best practices for continuous integration and deployment of ML models. Develop dashboards and visualizations to communicate insights and performance results.

Required Skills & Qualifications 37 years

of experience as a Data Scientist or Machine Learning Engineer. Strong hands-on experience with

Databricks

(including notebooks, Delta Lake, and MLflow). Advanced proficiency in

Python

(NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, etc.). Solid experience with

Azure Cloud Services

(Azure ML, Data Factory, Synapse, Blob Storage). Strong

SQL

skills for data extraction, transformation, and analysis. Experience building and deploying

ML models

in production environments. Understanding of

data pipelines, feature engineering, and model evaluation techniques . Familiarity with

MLOps

concepts and version control (Git/GitHub). Excellent problem-solving and communication skills; ability to explain complex concepts to non-technical stakeholders.

Preferred Qualifications Masters or PhD in

Computer Science, Data Science, Statistics, Applied Mathematics , or related field. Experience with

Power BI

or

Tableau

for data visualization. Knowledge of

Big Data tools

(Spark, Hive) or

other cloud platforms

(AWS, GCP). Experience in

natural language processing (NLP)

or

generative AI

is a plus.