Senior Data Scientist - Healthcare

Join us. Let’s make a direct impact in healthcare.

Being an Iodine employee means becoming part of something bigger - using clinical AI technology to drive smarter healthcare processes and positively impact patient care.

Who we are:

Recognized as one of Austin’s best places to work, we are a collaborative and dedicated team with innovation built into our DNA. Iodine is an enterprise AI company that is championing a radical rethink of how to create value for healthcare professionals, leaders, and their organizations - by automating complex clinical tasks, generating insights and empowering intelligent care. Powered by one of the largest sets of clinical data and use cases available, our groundbreaking clinical machine-learning engine, Cognitive ML, constantly ingests the patient record to generate real-time, highly focused, predictive insights that clinicians and hospital administrators can leverage to dramatically augment the management of care delivery.

What we're looking for:

Iodine thrives on innovation. We are looking for a Senior Data Scientist that will help us discover the information hidden in vast amounts of data. You will be joining a small team that is tackling many interesting healthcare problems using ML. Because we work on the cutting edge of a lot of technologies, we need someone who is a creative problem solver, resourceful in getting things done, and productive working independently or collaboratively. You will be accessing and shaping our enormous amount of data to help drive our future innovation.

What you'll do:

Work with a team of passionate data scientists to further the mission of Iodine and the Data Science team. Collaborate with teams, including both technical and business teams, from different functional areas to solve complex problems.  Develop statistical and machine learning algorithms, named entity recognition/named entity linking models, inference rules, probabilistic models, simulation models, and visualizations for client pilots and scaled solutions.  Lead multiple projects in parallel and assist other team members and conduct directed research and development in natural language processing and applied machine learning on healthcare datasets.

Present results and overviews to internal and external audiences and serve as a mentor to junior team members. Consult with business teams to provide guidance and capture feedback as required.  Perform exploratory data analysis (EDA), data profiling, and data cleaning on a variety of datasets.  Learn and identify data relationships across multiple contributing sources, developing and discovering direct and inferred data relationships where rules can be defined and consistently applied, and other strategies to optimize the efficiency and quality of the data being collected, normalized, and delivered.  Acquire data from primary or secondary data sources to maintain data quality programs, and leverage these sources to identify and interpret trends or patterns in complex datasets.  Create innovative frameworks and solutions for extracting value from client data. 

What we'd love to see:

• 7+  years hands-on experience in machine learning, statistics, and data analysis

• Ability to effectively communicate technical concepts to both technical and non-technical staff members

• Self-motivated and self-directed, able to learn new technologies quickly and adapt to a rapidly changing environment

• Proficiency in ML/Data Science languages and tools including Python (and packages including but not limited to Jupyter notebooks, pandas, numpy, scikit-learn, pytorch) and SQL

• Proficiency in using SQL and noSQL databases, including PostgreSQL, ElasticSearch

• Proficiency in NLP tools including, spaCy, nltk

• Superb coding, scripting, and software engineering experience and skills

• Master’s Degree or PhD strongly preferred in Computer Science, Statistics, Mathematics, Econometrics, Operations Research, Physics or a related field with a substantial research component and focus on data analysis

• Ability to demonstrate proficiency in machine learning, statistics, data analysis. Must have an excellent knowledge of advanced methods, and experience in applying those methods to a variety of problems

• Solid grasp of probability, statistical or mathematical modeling with analytical and quantitative problem-solving ability. Experience with healthcare data is strongly preferred.

• Demonstrated experience in applying machine learning to real-world problems

• Familiarity with software development cycles, version control systems (including Git), interacting with RESTful APIs, Mac and Linux platforms 

• Familiarity with ETL tools and proce