Data Science Intern

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

We are looking for a Data Science Intern who will support our product, sales, leadership and marketing teams with insights gained from analyzing cloud data.

This is a unique opportunity to get in on the ground floor of a new multi-disciplined team of experienced individuals who will be driving the solution design, development, and deployment of advanced machine learning solutions supporting the company’s digital medicine program and other mobile health applications.

The position is within Sikka Artificial Intelligence Lab’s team, which contributes to our autonomous diagnosis, health outcomes and inferencing technology strategy as well as our self-driving practice initiative.

The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams, from databasing and APIs to user engagement data. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Responsibilities:

• Provide insights into machine learning techniques focused on classification, supervised learning, reinforced learning and eventually deep learning
• Produce new and creative ML solutions in a landscape may include neural networks, with specific interest and emphasis on classification, supervised and unsupervised learning leading to deep learning systems, computer vision, human-computer interaction
• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Develop custom data models and algorithms to apply to data sets
• Coordinate with different functional teams to implement models and monitor outcomes
• Develop processes and tools to monitor and analyze model performance and data accuracy

Desired technical expertise:

• Strong problem solving skills
• Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques

We’re looking for someone in the midst of completing their Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field and is familiar with the following software/tools:

• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc.
• Knowledge/Experience querying databases and using statistical computer languages: R, Python
• Knowledge/Experience using web services: Spark, S3, RedShift, etc.
• Knowledge/Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Knowledge/Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL
• Knowledge/Experience with NoSQL databases, such as MongoDB, Neo4J, Neptune, Cassandra, HBase and associated languages (Cypher, Gremlin)