Business System Analyst - Remote Job.

Bertoni Solutions•San Jose, CA

22h•$20•Remote

About The Position

We are looking for a Business System Analyst with experience within the CRO (Contract Research Organization), pharmaceutical, biotechnology, healthcare or life sciences industry to work 100% remote. This is a full-time, remote nearshore opportunity for a U.S based client (outsourcing model, process managed by Bertoni) in the CRO (Contract Research Organization) industry. CROs provide clinical trial management, regulatory support, data management, and other research-related services to pharmaceutical, biotechnology, and healthcare companies, helping them develop and bring new therapies to market.

Requirements

5+ years as a Business Analyst, Business Systems Analyst or Systems Analyst.
Experience with data integration requirements, field mapping, and business rules.
Strong data quality analysis and agile delivery experience.
Experience working in clinical research, pharmaceutical, life sciences, biotechnology or regulated industries.
Understanding of clinical trial operations and the data generated across the study lifecycle, with particular focus on the feasibility and site selection phase.
Familiarity with at least several of the data sources in scope: CTMS, EDC, IRT, Medidata, Citeline, ClinicalTrials.gov, or equivalent clinical data platforms.
Understanding of what drives investigator and site selection decisions in a CRO context, including the role of historical performance data, competitive benchmarks, and standard of care alignment.
Able to understand schemas, APIs, and basic SQL.
Able to create data/process flow documentation.
Comfortable analyzing large, multi-source datasets.
Familiar with MDM concepts
Experience with Project Management tools like Jira, Azure DevOps, or OnePlan.
+5 years of experience as a Business Analyst, Business Systems Analyst or Systems Analyst.
Hands on experience with Jira, Agile/Scrum, Azure DevOps or OnePlan.
Experience working at CRO (Contract Research Organization), pharmaceutical, biotechnology, healthcare, or life sciences companies.
Advanced written and spoken English fluency is a MUST HAVE (from B2 level to C1/C2)
MUST BE located in Central or South America, as this is a nearshore position (Please note that we are not able to consider candidates requiring relocation or those located offshore).

Nice To Haves

Experience with clinical, survey, SaaS, EDC/CTMS, or site intelligence platforms.
Familiarity with Azure, Databricks, pipelines, GxP/CSV, and lakehouse concepts.
Wireframing/mockup experience and BA-related certifications preferred.

Responsibilities

Own the definition and documentation of data integration requirements between Partex.AI and each internal and external data source.
Document for each integration: what data is being exchanged, the direction of flow (inbound to Partex, outbound, or bi-directional), the triggering mechanism (scheduled batch, event-driven, API call), the key fields and their expected format, transformation or mapping logic, and how conflicts or missing values should be handled.
Identify and document which integrations must be built against the existing SQL Server Data Warehouse versus Databricks, and maintain a clear transition plan as the DWH-to-Databricks migration progresses.
Translate integration requirements into specifications that the Data and Technology integration team can implement, at a level of detail that leaves no ambiguity about source fields, target fields, or business rules.
Sequence integrations by business priority, distinguishing between what is needed for initial platform value versus what can follow in later phases.
For each data domain flowing into Partex.AI (investigator identity, site performance, enrollment history, country benchmarks, survey responses), identify which source system holds the authoritative version of that data.
Document conflicts where the same data field is available from multiple sources (e.g., investigator enrollment history from CTMS vs. Medidata) and work with stakeholders to define the resolution rule: which source wins, under what conditions, and whether blending is appropriate.
Support the Partex.AI MDM and deduplication configuration by articulating the business rules that should govern how investigator and site records are matched and merged across internal and external sources.
Flag data quality issues in source systems that will affect the quality of intelligence outputs in Partex.AI, and work with data owners to define remediation paths.
Work closely with Product Managers and clinical operations stakeholders to translate feasibility workflow needs into platform requirements, user stories, and acceptance criteria.
Participate in discovery sessions with feasibility, business development, and site selection teams to understand how intelligence outputs are used, what data combinations drive decisions, and where current manual processes create quality or speed failures.
Analyze current-state feasibility processes to identify where data gaps, integration failures, or missing feedback loops are driving the operational issues documented in the platform business case: lost awards, rework rates, and extended site selection timelines.
Produce process flow and data flow documentation that maps how data moves from source systems through Partex.AI to the end user workflows supporting RFP response, site identification, and site selection.
Define acceptance criteria for integrations and platform configurations that are testable by clinical operations users in UAT, not just technically verifiable by engineers.
Serve as the primary requirements interface with the Partex.AI (Innoplexus) implementation team, ensuring that integration specifications are clearly communicated and that vendor-delivered integrations conform to documented requirements.
Assess Partex.AI out-of-the-box capabilities against the client’s integration and data requirements and clearly document the gap between what the platform provides natively and what requires configuration or custom integration work.
Track integration delivery against the Q2-Q4 2026 implementation timeline and flag risks or dependencies to the Product Manager and Data and Technology leads.
Support the evaluation of Alchemer Enterprise integration requirements, ensuring that survey response data and scoring outputs flow correctly into Partex.AI and that cross-survey intelligence is accessible for site selection decisions.
Monitor integration health and data quality in Partex.AI outputs, working with Data and Technology to diagnose and resolve issues when platform intelligence does not match expected source data.
Maintain integration documentation as a living artifact, updated when source systems change, new data sources are added, or business rules are revised.
Support UAT and validation activities by producing requirements traceability documentation that maps platform behaviors back to defined integration and data requirements.
Identify opportunities to expand the platform's data foundation over time, including new external sources, additional internal operational data, and feedback loop data from completed studies.