Data Scientist

Role Overview

This position requires professional expertise in data science using Python and associated mathematical libraries, with an emphasis on machine learning model construction and deployment. The candidate will work on advanced machine learning frameworks and collaborate within sizable teams in a fast-paced setting.

Key Responsibilities

• Develop and utilize Python data processing and mathematical tools such as NumPy, Pandas, Scikit-learn, Seaborn, PyCaret, and Matplotlib for data analysis.
• Employ machine learning frameworks including but not limited to TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML, and OpenAI.
• Collaborate efficiently within large teams using tools like Git, Jira, and Confluence to manage workflows and communications.
• Leverage knowledge of cloud platforms such as AWS, Azure, or Google Cloud for deployment and data management.
• Apply familiarity with the pharmaceutical commercial landscape and patient data analytics to enhance project outcomes.
• Demonstrate a proactive learning attitude, resilience in challenging scenarios, and commitment to delivering results within deadlines.
• Provide mentorship and leadership to medium and large-sized teams, guiding them through project execution and problem-solving.

Requirements

• Strong experience working with Apache Spark utilizing Scala, Python, or Java languages.
• Expertise in building, training, evaluating, and deploying advanced machine learning models.
• Sound knowledge of statistical and probabilistic techniques such as Support Vector Machines, Decision Trees, Bagging, Boosting methods, and clustering algorithms.
• Proficiency in core natural language processing tasks including text classification, named entity recognition, topic modeling, and sentiment analysis.
• An understanding of generative AI concepts, large language models, and transformer architectures is advantageous.