AssureCare believes the foundation of a healthier community is built on empathy and a sense of urgency. We are seeking a Senior Data Scientist to help us build healthier communities through our enterprise care management software solution. If you are interested in joining a fast-growing software company delivering increased efficiency and efficacy to clients and improving patient outcomes, AssureCare is looking for motivated, team-oriented Individuals ready to make a powerful Impact in the healthcare industry.
- Guide and inspire the organization about the business potential and strategy of artificial intelligence
- Identify data-driven/ML business opportunities
- Prioritize, scope, and manage data science projects and the corresponding key performance indicators (KPIs) for success
- Define and communicate governance principles
- Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA)Machine Learning
- Generate hypotheses about the underlying mechanics of the business process
- Test hypotheses using various quantitative methods
- Display drive and curiosity to understand the business process to its core
- Network with domain experts to better understand the business mechanics that generated the data
- Apply various ML and advanced analytics techniques to perform classification or prediction tasks
- Integrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction etc.
- Testing of ML models, such as cross-validation, A/B testing, bias and fairness
- Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options
- Integrate model performance management tools into the current business infrastructure
- Implement champion/challenger test (A/B tests) on production systems
- Continuously monitor execution and health of production ML models
- Establish best practices around ML production infrastructure
- Train peers on specialist data science topics
- Network with internal and external partners
- Upskill yourself (through conferences, publications, courses, local academia and meetups).
Skills / Qualifications:
- Coding knowledge and experience in several languages: for example, R, Python/Jupyter, SAS, Java, Scala, C++, Excel, MATLAB, etc.
- Experience with popular database programming languages including SQL, PL/SQL, for relational databases and upcoming nonrelational databases such as NoSQL/Hadoop-oriented databases such as MongoDB, Cassandra, and others.
- Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Kafka, also MySQL, and so on
- Experience of working across multiple deployment environments including [cloud, on-premises and hybrid], multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service, and others.
Machine Learning and Data Science Knowledge/Skills
- Experience in one or more of the following commercial/open-source data discovery/analysis platforms: [RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
- Expertise in solving [vision, text analytics, credit scoring, failure prediction, propensity to buy] problems is preferable.
- Knowledge and experience in statistical and data mining techniques: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
Interpersonal Skills and Characteristics
- All candidates must be self-driven, curious and creative.
- They must demonstrate the ability to work in diverse, cross-functional teams in a dynamic business environment.
- Candidates should be confident, energetic self-starters, with strong moderation and communication skills.
- Candidates should exhibit superior presentation skills, including storytelling and other techniques to guide and inspire.
- Ability to lead a team and influence others
- Candidates should have 3-6 years of relevant project experience in successfully launching, planning, and executing data science projects.
- A specialization in text analytics, image recognition, graph analysis or other specialized ML techniques such as deep learning, etc., is preferred.
- Ideally, the candidate is adept in agile methodologies and well-versed in applying DevOps/MLOps methods to the construction of ML and data science pipelines.
- Candidates should ideally exhibit project experience in applying ML and data science to business functions
- Candidates need to demonstrate that they were instrumental in launching significant data science projects.
- Candidates should have demonstrated the ability to manage large data science projects and diverse teams.
- A bachelor’s or master’s degree in computer science, data science, operations research, statistics, applied mathematics, healthcare or a related quantitative field [or equivalent work experience such as, economics, engineering and healthcare] is [preferred/required]. Alternate experience and education in equivalent areas such as healthcare, engineering or physics, is acceptable. Experience in more than one area is strongly preferred.
- Candidates will ideally have a specialization in ML, AI, cognitive science or data science.
AssureCare® is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and internship. AssureCare® makes hiring decisions based solely on qualifications, merit, and business needs at the time. Furthermore, the Company will make reasonable accommodations for qualified individuals with known disabilities unless doing so would result in an undue hardship.