Jobs at Beghou Consulting

As an Associate Consultant, you will manage Data Warehousing projects, design data models, assist in project management, mentor team members, and ensure data quality for informed decision-making.

Supports pharmaceutical client engagements by analyzing complex datasets, developing data-driven solutions, and creating analytical visualizations. Uses R, Python, SQL, Tableau, Excel, SAS, and Power BI while collaborating with project leads and global stakeholders. Responsibilities include solving business problems, preparing client deliverables and documentation, applying quality controls, managing assigned tasks, and ensuring timely, accurate project outcomes and client satisfaction.

Build and deploy AI features for document understanding, structured extraction, and review workflows. Develop LLM pipelines with validation, retrieval, structured generation, and human review. Evaluate and improve model quality, reliability, latency, and cost in production. Integrate AI services into APIs and applications while documenting system behavior and limitations. Collaborate with product, design, engineering, and life sciences domain experts to create practical AI capabilities.

Lead full-stack product development from discovery through production. Build accessible React and TypeScript interfaces, backend APIs and services, data models, and reliable workflows. Partner with product and design, improve performance, security, reliability, and observability, investigate production issues, review code, mentor engineers, and establish engineering practices. The role requires substantial experience delivering data-heavy applications and features from ambiguous requirements to production.

Consults on Master Data Management and data warehousing projects for life sciences clients. Responsibilities include designing data models, developing MDM solutions, managing data quality and governance, documenting ETL processes, conducting reviews, coordinating distributed teams, mentoring junior staff, and supporting project leadership. The role requires customer and address mastering, pharma data-source familiarity, Python, SQL, data profiling, requirements translation, and experience with MDM platforms.

Develop and maintain enterprise applications using .NET and C#. Build RESTful APIs and microservices, write SQL Server queries and stored procedures, debug defects, participate in code reviews and Agile ceremonies, and collaborate with product, senior engineering, and QA teams. The role emphasizes learning Microsoft technologies, applying coding standards, and contributing to scalable, secure, high-performance solutions.

Develop and maintain enterprise applications using .NET Core, .NET 8+, and C#. Build REST APIs and microservices, write tests, optimize SQL Server queries, and support Azure-based deployments. Participate in code reviews, Agile ceremonies, debugging, CI/CD, and collaborative requirements gathering while learning Microsoft ecosystem best practices.

Administer commercial agreements from intake through approval, signature, and ongoing contract management. Maintain CLM records, track renewals and obligations, prepare summaries, support audits and due diligence, coordinate stakeholders, and escalate issues requiring legal judgment. The role also improves contract procedures, templates, workflows, and automation while handling confidential information.

Leads data-driven commercial operations and analytics projects for pharmaceutical and life sciences clients. Responsibilities include managing cross-functional teams, defining project scope, analyzing data, developing insights and deliverables, optimizing data processes with coding, managing client communications, supporting business development, and mentoring junior consultants.

Associate Consultant responsible for leading Master Data Management and data warehousing projects, including data modeling, ETL processes, data quality, customer and address mastering, documentation, code reviews, task planning, client communication, and team mentorship. The role requires translating business requirements into scalable MDM solutions using Python, SQL, and platforms such as Reltio or Informatica MDM, primarily for life sciences clients.

Supports Master Data Management and data warehousing projects by designing data models, developing and documenting ETL processes, applying data quality and standardization rules, and analyzing client requirements. Coordinates task planning, project delivery, code and design reviews, client communications, and offshore collaboration. Requires experience with customer and address mastering, data governance, data profiling, Python, SQL, and MDM platforms such as Reltio or Informatica.

Consults on Master Data Management and data warehousing projects for life sciences clients. Responsibilities include designing data models, developing MDM and ETL solutions, managing data quality and governance, documenting architectures, reviewing code, coordinating project tasks, communicating with clients, mentoring team members, and supporting project planning and risk mitigation. Requires expertise in customer and address mastering, pharmaceutical data sources, Python, SQL, and MDM platforms.

Lead life sciences commercial operations and analytics consulting projects from scoping through delivery. Manage cross-functional teams, client communications, timelines, resources, and data analytics tasks. Analyze data, develop actionable insights, optimize data processes using coding, and create reporting deliverables. Support business development, collaborate with global teams, and mentor junior consultants while providing strategic guidance and thought leadership.

Provide advanced analytics and AI/ML support for life sciences clients, particularly pharmaceutical commercialization initiatives. Lead India-based delivery teams, manage complex analytical projects, develop client recommendations, enhance consulting services, and support business development. The role requires hands-on work with Python, visualization tools, cloud platforms, and pharmaceutical use cases, along with mentoring, stakeholder collaboration, and communication with US clients.

Leads cross-functional data management and analytics projects for pharmaceutical and life sciences clients. Responsibilities include data warehouse development, ETL and schema design, data analysis, process optimization, client communication, project management, business development, and mentoring junior staff. The role also provides strategic guidance, develops reporting solutions, manages timelines and resources, and contributes to internal data platform initiatives.

Supports consulting projects and client deliverables through business analytics, data organization, reporting, dashboard preparation, project coordination, stakeholder communication, and process improvement. The role tracks milestones, documents meetings, follows up on action items, manages multiple assignments, and contributes to operational and strategic initiatives across internal and global teams.

The Manager of Commercial Operations & Analytics will lead client engagements, manage projects, enhance data processes, and drive client relationships within the life sciences sector.

Leads the design and implementation of Snowflake-based data management solutions for life sciences clients. Translates business requirements into data models, technical designs, transformation logic, and implementation plans; owns technical workstreams through deployment; and delivers ingestion, transformation, warehousing, reporting, testing, and operational readiness. The Consultant troubleshoots complex data issues, advises clients, mentors junior team members, contributes to project planning, and develops scalable data engineering best practices.

Leads commercial operations and analytics engagements for life sciences and pharmaceutical clients. Responsibilities include project and team leadership, data process enhancements, analytics and reporting oversight, client relationship management, proposal development, project financial management, business growth initiatives, and mentoring. The role requires pharma commercial expertise across data management, sales operations, commercial analytics, and BI/reporting, plus coding and data visualization skills.

Lead a team of data scientists to leverage analytics and machine learning in the life sciences sector, optimizing outcomes through data-driven insights.