Data Architect Role with Pharma Domain

Role : Data Architect Role with Pharma Domain

Rate: $75-78/hr.

Client Full Address: LAKEWOOD 44107, OH

Remote / WFO / Hybrid: Hybrid

Hire Type (FTE/Contract): Both

Project Duration: 1 year

Indent ID: PSL310833-15

Required Skills:

· Programming: Proficiency in Python, R, and SQL.

· Math and Stats: Strong background in statistics, probability, and algebra.

· Tools: Experience with data frameworks, big data tools, and visualization software like Tableau or Power BI.

· Education: Bachelor's or master's degree in computer science, Math, Statistics, Engineering, or a related quantitative field.

Mandatory Skills

· Knowledge / Good understanding of PubMed Data

· Experience as Disease management SME

· Experience in Scrum

· Some Alteryx & Snowflake experience

Familiarity with:

· PubMed, its data, MeSH structure

· Clinical trials data, clinicaltrials.gov

· Claims: Mx and Rx data, ICD10 codes, taxonomies, CPT, NDC (less important than PubMed)

· JIRA/Confluence

· Alteryx Gallery and Designer

· Tableau desktop, Curator

Role & Responsibilities:

· Oversee the completion of projects from internal kickoff, development, delivery, and continuing support

· Coordinating with other teams to ensure the scope of the project is correct/meeting client's expectations

· Manage development and other teams

· Set up and run internal workflows and manage data as it is modified per project.

· Ensure project data is prepared and uploaded to client inface in a timely manner

· Maintain project refresh schedule

· Interface with vendors: order profile information, conference abstracts

· Troubleshoot data issues on a project-by-project basis

· Collaborate with Product department on potential updates to the deliverable

Looking for below Technical Domain Expertise under Health Care sector.

· Data Collection: Gather structured and unstructured data from internal and external sources.

· Data Cleaning: Process, verify, and clean data to ensure accuracy.

· Model Building: Design and train machine learning models and predictive algorithms.

· Analysis: Run exploratory data analysis to find hidden trends and patterns.

· Communication: Share findings with company leaders using clear reports and visual dashboards