Data Sceintist - AI​/ML Engineer

Overview
We are seeking a highly skilled  Data Scientist  to advance our analytics and AI strategy. This role focuses on designing and delivering  automated AI solutions  powered by robust statistical modeling, scalable data engineering, real‑time analytics, and impactful data visualization. The ideal candidate has experience with  Python ,  SQL ,  Azure Databricks ,  Snowflake ,  Tableau , applied statistics, strong business acumen, and expertise in integrating disparate datasets into unified analytical views.

Key Responsibilities
Develop, deploy, and maintain  machine learning  and  statistical models  that power automated, scalable AI solutions.
Build end‑to‑end  automated AI pipelines , including data ingestion, feature engineering, model training, deployment, and continuous monitoring.
Write clean, efficient  Python  code and build distributed data processing workflows in  Azure Databricks  using Spark.
Use  SQL  across  Snowflake  and Azure data platforms to extract, transform, join, and analyze large datasets.
Apply  applied statistics , including hypothesis testing, regression modeling, experimental design, and probability, to support data-driven decisions.
Integrate  disparate data tables and sources  to create a comprehensive  360° view of the customer , including support for  near-time or real-time data updates .
Design insightful  Tableau dashboards  and visualizations for both technical and business audiences.
Work closely with stakeholders to translate business needs into analytical solutions that drive measurable outcomes.
Explore and operationalize emerging  AI/ML techniques , such as LLMs, NLP, embeddings, and generative AI.
Ensure high standards of data quality, governance, and responsible AI throughout all modeling workflows.
Work within and across the  Azure ecosystem , including Azure Data Lake, Azure Machine Learning, Azure Data Factory, and related services.

Required Qualifications
Advanced degree (Master’s or PhD)  in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related analytical field.
Strong proficiency in  Python  (pandas, Num Py, scikit‑learn, PySpark).
Expert-level  SQL  skills and experience with  Snowflake  in production environments.
Hands-on experience with  Azure Databricks , Spark, and Delta Lake.
Broader experience with  Azure cloud services  such as Azure Data Lake, Azure Machine Learning, and Azure Data Factory.
Experience building or contributing to  automated AI/ML solutions .
Proficiency in  applied statistical methods , including regression, statistical testing, sampling, and model evaluation.
Advanced experience in  data visualization and dashboard development  using Tableau.
Ability to integrate data from multiple sources to form unified analytical views ideally with  real-time or streaming data  components.
Strong  business acumen , with the ability to convert insights into strategic recommendations.

Preferred Qualifications

Experience with  MLOps , CI/CD pipelines, or ML model monitoring frameworks.
Familiarity with  deep learning  (Tensor Flow, PyTorch) or  generative AI  frameworks.

Experience with data streaming technologies (e.g., Azure Event Hub, Kafka).
Knowledge of  LLM fine-tuning , vector search, and modern AI architectures (e.g., RAG).
Ability to communicate complex concepts through compelling data stories.