For over 30 years, Beghou Consulting has been a trusted adviser to life science firms. We combine our strategic consulting services with proprietary technology to develop custom, data-driven solutions that allow life sciences companies to take their commercial operations to new heights. We are dedicated to client service and offer a full suite of consulting and technology services, all rooted in advanced analytics, to enhance commercial operations and boost sales performance.
You will play a key role in designing, developing, and deploying AI solutions tailored to pharmaceutical clients. You will collaborate with cross-functional teams including data scientists, business consultants, and software developers to translate complex life sciences challenges into AI-driven innovations
We'll trust you to:
- Design and implement AI/ML pipelines that solve real-world problems in life sciences (e.g., territory alignment, rep scheduling, patient segmentation, incentive compensation optimization).
- Work closely with domain consultants to understand client requirements and develop tailored AI solutions.
- Lead efforts in data ingestion, feature engineering, and model development across structured and unstructured data sources (e.g., sales data, KOL feedback, medical claims).
- Build and deploy scalable AI services and LLM-based copilots (e.g., for field force, MSLs, or commercial analytics teams).
- Implement GenAI and Agentic AI frameworks for commercial automation.
- Conduct technical reviews and provide mentoring to junior AI team members.
- Collaborate with DevOps and cloud teams to deploy models on AWS/Azure.
- Present technical concepts and outcomes to internal stakeholders and client teams.
You'll need to have:
- 7+ years of experience in AI/ML engineering, with at least 1-2 years in a client-facing or consulting role.
- Proficient in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow, LangChain, Hugging Face).
- Experience building and deploying machine learning models in production.
- Strong understanding of MLOps tools and practices (e.g., MLflow, Docker, Git, CI/CD).
- Exposure to LLMs, transformers, and retrieval-augmented generation (RAG) techniques.
- Experience working with cloud environments (AWS, Azure preferred, Databricks).
- Excellent communication skills with the ability to explain complex technical ideas to non-technical stakeholders.
- Bachelor's/Master's in Computer Science, Data Science, Engineering, or related field.
What you should know:- We treat our employees with respect and appreciation for both their contributions and their individuality.- We value our employees' diverse talents and abilities, fostering a supportive, collaborative, and dynamic work environment that encourages professional and personal growth.- You will have the opportunity to collaborate with and learn from colleagues at all levels of the organization, promoting teamwork and success in every project.- We have had steady growth throughout our history because the people we hire are committed not only to delivering quality results for our clients but also to becoming leaders in sales and marketing analytics.Apply for this job
