Digital Customer Engagement AI Data Scientist
The IT Data Architect designs, creatse, deploys and manages an organization's data architecture
▪Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture
Key Responsibilities
AI & Data Science
• Design, build, and deploy machine learning and AI models (predictive, prescriptive, and generative) to solve real business problems.
• Apply advanced statistical, ML, and deep learning techniques to structured and unstructured data.
• Develop and maintain end‑to‑end data science pipelines, from data ingestion and feature engineering to model training and evaluation.
• Collaborate with data engineering teams to ensure scalable, reliable, and well‑governed data foundations.
Production & MLOps
• Operationalize AI solutions using MLOps best practices (model versioning, monitoring, drift detection, retraining).
• Ensure AI models meet enterprise requirements for performance, robustness, security, and maintainability.
• Support cloud‑based AI platforms (e.g., Azure‑based ML environments) used across the organization.
Responsible & Compliant AI
• Embed ethical AI principles, transparency, and governance into model design and deployment.
• Ensure compliance with internal AI governance frameworks and applicable regulations (e.g., data privacy, AI risk management).
• Act as a trusted advisor on responsible AI usage for stakeholders.
Business & Stakeholder Collaboration
• Translate business needs into data science problem statements and measurable success criteria.
• Communicate complex analytical results clearly to non‑technical audiences.
• Partner with product owners, process owners, and IT leaders to drive adoption and value realization.
Required Qualifications
• Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, AI, or a related field.
• Strong hands‑on experience with Python and common data science libraries (e.g., pandas, NumPy, scikit‑learn, PyTorch/TensorFlow).
• Solid understanding of machine learning algorithms, model evaluation, and statistical methods.
• Experience working with SQL and large‑scale datasets.
• Practical experience deploying models in production or near‑production environments.
Preferred Qualifications
• Experience with cloud‑based data & AI platforms (e.g., Azure Machine Learning, Databricks, Snowflake).
• Familiarity with Generative AI / LLM use cases, prompt engineering, or vector databases.
• Exposure to enterprise data governance and regulated environments.
• Experience collaborating in cross‑functional, global teams.
• Previous work in highly regulated environments specific to healthcare and healthcare medical technology.
Career Path
This role can evolve into Senior AI Data Scientist, AI Product Lead, Principal Data Scientist, or Data & AI Architecture / Strategy roles, depending on strengths and interests.
• Develop strategies for data acquisitions, archive recovery, and implementation of a database
• Clean and maintain the database by removing and deleting old data with the help of the team(s)
• Define how data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way
• Set data architecture principles, create models of data that enable the implementation of the intended business architecture, create diagrams showing key data entities, and create an inventory of the data needed to implement the architecture vision
• Ensure compliance to Q, ISEC and DP regulations
The base pay range for this position is:
$143,900 - $197,868
Factors which may affect starting pay within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate.
If this is a commission eligible position the commission eligibility will be in accordance with the terms of the Company's plan. Commissions are based on individual performance and/or company performance.
The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan. life insurance, long-term and short-term disability insurance, paid parking/public transportation, paid time off, paid sick and safe time.
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▪Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture
Key Responsibilities
AI & Data Science
• Design, build, and deploy machine learning and AI models (predictive, prescriptive, and generative) to solve real business problems.
• Apply advanced statistical, ML, and deep learning techniques to structured and unstructured data.
• Develop and maintain end‑to‑end data science pipelines, from data ingestion and feature engineering to model training and evaluation.
• Collaborate with data engineering teams to ensure scalable, reliable, and well‑governed data foundations.
Production & MLOps
• Operationalize AI solutions using MLOps best practices (model versioning, monitoring, drift detection, retraining).
• Ensure AI models meet enterprise requirements for performance, robustness, security, and maintainability.
• Support cloud‑based AI platforms (e.g., Azure‑based ML environments) used across the organization.
Responsible & Compliant AI
• Embed ethical AI principles, transparency, and governance into model design and deployment.
• Ensure compliance with internal AI governance frameworks and applicable regulations (e.g., data privacy, AI risk management).
• Act as a trusted advisor on responsible AI usage for stakeholders.
Business & Stakeholder Collaboration
• Translate business needs into data science problem statements and measurable success criteria.
• Communicate complex analytical results clearly to non‑technical audiences.
• Partner with product owners, process owners, and IT leaders to drive adoption and value realization.
Required Qualifications
• Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, AI, or a related field.
• Strong hands‑on experience with Python and common data science libraries (e.g., pandas, NumPy, scikit‑learn, PyTorch/TensorFlow).
• Solid understanding of machine learning algorithms, model evaluation, and statistical methods.
• Experience working with SQL and large‑scale datasets.
• Practical experience deploying models in production or near‑production environments.
Preferred Qualifications
• Experience with cloud‑based data & AI platforms (e.g., Azure Machine Learning, Databricks, Snowflake).
• Familiarity with Generative AI / LLM use cases, prompt engineering, or vector databases.
• Exposure to enterprise data governance and regulated environments.
• Experience collaborating in cross‑functional, global teams.
• Previous work in highly regulated environments specific to healthcare and healthcare medical technology.
Career Path
This role can evolve into Senior AI Data Scientist, AI Product Lead, Principal Data Scientist, or Data & AI Architecture / Strategy roles, depending on strengths and interests.
• Develop strategies for data acquisitions, archive recovery, and implementation of a database
• Clean and maintain the database by removing and deleting old data with the help of the team(s)
• Define how data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way
• Set data architecture principles, create models of data that enable the implementation of the intended business architecture, create diagrams showing key data entities, and create an inventory of the data needed to implement the architecture vision
• Ensure compliance to Q, ISEC and DP regulations
The base pay range for this position is:
$143,900 - $197,868
Factors which may affect starting pay within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate.
If this is a commission eligible position the commission eligibility will be in accordance with the terms of the Company's plan. Commissions are based on individual performance and/or company performance.
The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan. life insurance, long-term and short-term disability insurance, paid parking/public transportation, paid time off, paid sick and safe time.
Apply tot his job
Apply To this Job