Project Leader-Clinical Solutions CoE

Job Title: Clinical Data Scientist - Axtria Clinical Center of Excellence

Location:

Core Responsibilities:

Domain Experience

Skills and Experience

• Should have knowledge of Clinical R&D domain with hands on experience on data sources from one more clinical business functions e.g. Clinical Operations, Biometrics, Drug Safety, Medical Affairs, Real-World Data (RWD), Laboratory data, Regulatory data sources etc.
• Should have good understanding and hands-on experience on curating, analyzing, and mining data from very clinical data sources e.g. CTMS, EDC, IRT, Labs, EHR kind RWD sources. Should have working knowledge of CDISC clinical data standards e.g. CDASH, SDTM, ADaM, FHIR etc.
  

Technical Skills

• Proficient in developing models with Python/PySpark. Experience with Databricks or Dataiku DSS (Data Science Studio) platforms would be an advantage. Highly skilled in creating, testing, deploying, and maintaining state of the art AI/ML/GenAI solutions.
• Skilled in statistical and probabilistic methods e.g. SVM, Decision-Trees, Bagging, Boosting, Clustering, Time Series Analysis etc. Experience in core NLP techniques e.g. Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc.
• Experience/knowledge of LLMs, LSTMs, GRUs, transformers will be an advantage. Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence is expected. A good understanding of any of the cloud platforms AWS, Azure or GCP.
  

Soft Skills

• Work closely with cross-functional teams, including clinical data engineers, clinical data modelers, front end developers, QA/CSV specialists, clinical SMEs, project managers, and cloud/infrastructure professionals, to understand project requirements and deliver high-quality solutions.
• Maintain thorough documentation of methodologies, processes, and results of the models. Prepare and present detailed reports on assigned projects to stakeholders, including client and internal leadership illustrating the impact and effectiveness of data-driven strategies.
  

Qualifications

• A Master's or Ph.D. degree in Data Science, Computer Science, Statistics, Life Sciences, or a strong experience in clinical data science is preferred.
• 6 - 10 years of hands-on experience in data analysis, data mining, and predictive analytics, preferably within the context of clinical R&D.
• Strong understanding of clinical R&D processes in life sciences organizations and the data and technologies used in these processes.
• Proven programming skills in Python/PySpark. Experience with machine learning frameworks like TensorFlow, Keras, PyTorch, or Scikit-learn.
• Proficiency in using analytical and data visualization tools such as SQL, Tableau, Power BI, or similar platforms.
• Excellent communication skills with the ability to convey complex data-driven insights to non-technical stakeholders.
• Results-oriented mindset, with a focus on defining and measuring success and delivering tangible outcomes.
• High ethical standards and integrity, with a commitment to compliance and transparency.