The Data Scientist should be versed in statistics, predictive modeling, machine learning, computational simulation, geospatial modeling, network science, or other analytic techniques. The data scientist is expected to participate in the design, development, and implementation of novel analytics to address a variety of customer problem sets.

Responsible for driving communications between NeuMoDx groups and the Data Scientist team. A Data Scientist position is available immediately. - Work cross-functionally to develop and implement data analytics tools to support molecular biologist, engineers, and assay developers to interpret results.

2-4 years current professional experience as a Data Scientist with Machine Learning, Predictive Modeling, and Optimization. 2-4 years current professional experience as a Data Scientist with Marketing Mix Modeling (MMM) and advertising technology platforms.

To learn more about the Crime Lab and Education Lab, visit The RoleThe University of Chicago Crime Lab and Education Lab are seeking a data scientist to work on our portfolio of projects applying machine learning to public policy, particularly in the area of improving policing and police-community relations.

Must have at least three (3) years of experience with: Performing data analysis using coding languages (Python, SQL, SAS, R); Using knowledge of database design and schemas to understand and query new data sources; Using data visualization tools to create dashboards; Using knowledge of data analytics to inform root cause analysis, diagnostics and to conduct simulations; and Using MS Office applications including Excel.

JMP proficiency (SAS statistical tool) MATLAB experience Active TS/SCI clearance Basic Qualifications for a Sr. Principal Data Scientist: Bachelor's degree in a technical area with 9 years of relevant experience (7 years with technical MS; 4 years with a PhD in related field) Experienced in Microsoft Excel (Pivot tables, VLookup, etc.

Responsibilities Retrieve and process massive structured and unstructured datasets Build ML models and automated systems like recommendation and scoring tools Define comprehensive research approaches enabling rigorous assessmentsPerform statistical analysis and data mining to create predictive systemsVisualize insights using Microsoft Office, Tableau, Python, R Develop ML prototype solutions with TensorFlow, PyTorch etc.

Sr. Data Scientist. Provide knowledge, insight and guidance of third party data providers such as Transunion, Clarity/Experian and Equifax to include knowledge of products and data available, products to purchase or discontinue, cost benefit analysis of retrospective analysis, effective use of variables, data dictionaries as well as advantages and limitations.

We are currently seeking a qualified data scientist with substantial experience in spatiotemporal data analytics to join our GeoAI group within the Geographic Data Science Section of Geospatial Science and Human Security Division.

PhD Data Science, Computer Science, Cheminformatics, Bioinformatics, Epidemiology, Biology, Chemistry, Genomics with at least 2 years experience or Masters with 5 years experience. or PhD in Data Science, Computer Science, Cheminformatics, Bioinformatics, Epidemiology, Biology, Chemistry, Genomics and 2+ years of academic / industry experience.

Familiarity with cloud computing platforms (e.g., AWS, GCP) and big data technologies (e.g., Databricks) is a plus. The Cash App Quantitative Finance Team is an intellectually diverse team of machine learning modelers, data scientists, former strategy consultants and data engineers focused on applying leading AI, graph analytics and machine learning algorithms to solve business problems for executives within Cash App and the broader Block organization.

PhD with at least 6 years experience or Masters with 8 years experience (e.g. Data Science, Computer Science, Cheminformatics, Bioinformatics, Epidemiology, Biology, Chemistry, Genomics) Strong understanding of chemistry, molecular biology concepts, multi-dimensional omics data and modern approaches to data integration and data processing workflows Excellent programming skills in scientific languages such as R or Python.

Experience delivering data science projects from model development to production deploymentAny of the following qualifications is a plus Deep Learning algorithms (TensorFlow or Equivalent framework), ideally demonstrated by relevant industrial experienceExperience in deploying predictive or prescriptive data science solutions from any embedded electronic sensor data streams (such as IoT sensors, PLC systems, condition monitoring systems, wearables etc.

Coordinate with different functional agile teams such as data engineering and software development to deploy the data science solutions to production and integrate it with existing IT digital solutions and products Ideal Profile: Master’s degree in Applied Mathematics, Statistics, Machine Learning, Electrical Engineering, Computer Science/Information Systems or related fields or MBA with quantitative focus.

The primary focus will be in applying data mining techniques, doing advance statistical analysis, and building high quality machine learning or deep learning models and deploying them as productive solutions to get integrated with existing IT digital solutions and productsResponsibilities Lead discovery processes with business stakeholders to identify opportunities and business problems and framing them into an IT data science/ advanced data analytics project initiative.