What are the responsibilities and job description for the Sr. Artificial Intelligence - Data Analytics Engg. ( W2 or Salaried Only ) position at IRIS Software Group?
Our Client which is a large Pharma Co. is urgently looking to hire Sr. AI - Data Analytics Engg.
Sr. AI - Data Analytics Engg.
Location: Seattle, WA
Long Term Contract - 12 Months ( W2 or Salaried Only )
3 days onsite every week.
Our Client is seeking a highly experienced Senior AI- Data Analytics Engineer to serve as a key contributor in building advanced analytics infrastructure and AI-driven decision support tools for the Global Patient Operations Cell Therapy team. This role blends data engineering, analytics engineering, and AI/ML integration to enhance visibility into critical operations such as scheduling, clinical trials, and commercial performance.
The ideal candidate thrives in regulated environments, understands the nuances of healthcare data, and can own delivery end-to-end from data ingestion through to dashboarding and insight delivery.
Required Skills
Data Engineering, Data Science Concepts ( AI-ML Ops ), Strong Cloud ( AWS – Azure ), DBT, Python, PySpark, Tableau, Power BI, SQL.
Advanced analytics Scikit-learn, Tensorflow, Pytorch, ML Flow, feature engineering AI Tools OpenAI API, Langchain, Retrieval-Augmented Generation (RAG) MLOPs/Deployment ML Pipelines, CI/CD, Domino, monitoring/Logging
Responsibilities
- Design and build scalable data pipelines using python, SQL and cloud-based tools (Azure, AWS)
- Develop and maintain analytics models and data transformation using dbt, airflow and data warehouses (ex: Snowflake, BigQuery)
- Build and manage dashboards and data visualizations using web-based tools, Tableau, Power BI.
- Ensure data quality, governance and security compliance across engineering workflows
- Responsible for ingestion, integration and delivery of data products and insights across multiple platforms applying and maintaining data integrity and governance rules.
- Knowledge of deep learning methods for NLP (quantitative area of study, Comp Science preferred).
- Support adhoc analytics initiatives for clinical trials, commercial ops and digital health systems.
- Utilizes supervised or unsupervised methods, learning from vast amounts of unlabeled data to drive insight .
- Experience working with unstructured text.
- Develop high quality analytical and statistical models, insights, patterns, visualizations, that can be used to improve decision making in manufacturing operations.
- Responsible for documentation of all technical work both within and outside of formal document management systems.
Required Qualifications
- 5 Yrs of experience in data engineering, analytics or applied machine learning
- Strong python and SQL Skills, experience in ETL Orchestration tools (Airflow, Prefect. Domino).
- Solid grasp of data science fundamentals: causal inference, regression, classification, experimental design .
- Ability to manipulate and analyze complex datasets.
- Proficiency in modern data stack (dbt, snowflake/Big Query, version control, CI/CD pipelines).
- Experience and familiarity in DataOps/MLOps frameworks, AI/LLM tooling such as OpenAI ,Langchain, Hugging face Transformers etc.
- Strong communication and stakeholder engagement skills
- Experience in regulated industry (Pharma, biotech or life sciences) is highly preferred
Nice to Have
- Knowledge of GxP, HIPAA or compliance standards
- Experience with data modelling in clinical trials, real world evidence (RWE) or commercial analytics
- Familiarity with NLP, time series forecasting, or image analytics in healthcare.
- Master’s degree or PhD in Public Health, Economics, Statistics, Computer/Data Science, or related field
