Senior Data Scientist

In this role, you will work closely with our client data science  team to solve nominal and long tail perception, prediction, and planning problems through novel and advanced machine learning methods, including foundation models, out-of-distribution detection, imitation learning, and reinforcement learning. If you love solving challenging problems and deploying those solutions into the real world, come join us!

Would focus on using data analysis, statistical modeling, and machine learning techniques to extract insights from cancer research data. This includes analyzing clinical, genomic, and imaging data, developing predictive models, and collaborating with researchers to translate findings into actionable knowledge.

Key Responsibilities:

• Data Analysis and Interpretation:

• Gathering, cleaning, and transforming data from various sources (e.g., clinical records, genomic databases, imaging data).

• Conducting exploratory data analysis (EDA) to identify patterns, trends, and anomalies.

• Applying statistical methods and machine learning algorithms to analyze data and answer specific research questions.

• Model Development and Evaluation:

• Developing and implementing predictive models (e.g., for treatment response, disease progression, patient stratification).

• Modify or improve cancer detection models such as CHIEF, GALEN, ECgMLP.

• Evaluating the performance of models using appropriate metrics and validation techniques using PyTorch or Tensorflow frameworks .

• Solid experience with various deep learning models like CNN, RNN, GAN, DBN and ability to fine-tune them.

• Developing pipelines for data processing and model deployment.

• Collaboration and Communication:

• Working collaboratively with researchers, clinicians, and other data scientists to identify research needs and develop data-driven solutions.

• Communicating findings through presentations, publications, and reports.

• Mentoring and training junior researchers in data science methods.

• Infrastructure and Tool Development:

• Creating and maintaining data pipelines and infrastructure for data storage, processing, and analysis.

• Developing and implementing tools and workflows for data analysis and model development.

• Specific Skills:

• Strong programming skills in languages like Python, R, or C++.

• Experience with statistical software (e.g., SAS, SPSS, Stata).

• Familiarity with machine learning techniques (e.g., regression, classification, clustering, deep learning).

• Knowledge of cancer biology and relevant research areas.

• Experience with database management and data warehousing.

• Excellent communication and collaboration skills.

You have 4+ years of work experience with an M.Sc. or Ph.D. focusing on one or more of the following areas: Computer Science, Artificial Intelligence, Mathematics, or a closely related field

Demonstrated research publications in any of the major conferences (RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, etc.)