What are the responsibilities and job description for the Associate Principal, Analytics position at Trinity Life Sciences?
THIS ROLE IS LOCATED ON-SITE AT A CLIENT IN THOUSAND OAKS, CALIFORNIA
Trinity is seeking an Associate Principal to join and lead the team of data scientists managing multiple projects. The AP plays a unique role leading client engagement, establishing and promoting best practices, and being a culture carrier of the team. This individual has full oversight over project teams, builds and maintains client relationships, is responsible for best practices and innovation, and trains / mentors junior team members.
Essential Functions
- Serve as the main client point of contact for projects – from project kick off, internal and external meetings, to final deliverables.
- Design, develop and deliver Al / machine learning enabled solutions for our industry specific data analytics platform.
- Guide in building scalable solutions to collect, manipulate, present and analyze large datasets in a production environment.
- Provide guidance to software engineers for algorithm implementation for solution / product development.
- Experience managing real-time delivery and production pipelines on large scale datasets.
- Lead efforts in Data Engineering (DE) and Machine Learning Operations (ML Ops) and provide guidance on implementing the Gen AI Initiatives.
- Engage with clients at a strategic level, offering consulting services, and ensuring alignment of data science initiatives with their evolving business objectives.
- Conduct regular business review meetings and discussions to align data science initiatives with client objectives and ensure project success.
- Bachelor’s / master’s degree and minimum 8 years of professional experience is required
- Degree in applied math, statistics, machine learning or computer science. PhD / MS is preferred.
- Deep understanding of statistics and experience with machine learning algorithms / techniques
- Proven programming skills in particular SQL, Python(pyspark), ML Flow strong experience with DL frameworks such as TensorFlow, Kedro and others
- Scientific expertise and real-world experience in deep learning (CNN, LSTM, NLP) & ML models.
- Experience with software DevOps CI / CD tools, GitLab.
- Preferred to have experience with healthcare data, e.g., clinical trial data, electronic medical records, and insurance claims; or Biosciences data, e.g., protein or small molecule data, or bioinformatics; or Biopharmaceutical manufacturing.
- Facilitate ML & Data engineering efforts by architecting and guiding the implementation of data and ML pipelines for development and deployment.
- Ability to work productively with team members, identify and resolve tough issues in a collaborative manner.
- Experience in applying machine learning techniques to real-world problems in a production environment.
- Utilize expertise in integrating and leveraging Gen AI LLMs to maximize operational efficiency.
- Experience in conducting test and control analysis and implementing optimization algorithms (Genetic Algorithms).
