Learning Scientist Resume Sample
Domenic Boyer
57716 Jeffrey Wall,
New York,
NY
+1 (555) 414 1698
Work Experience
Senior Deep Learning Scientist Speech
11/2017
-
PRESENT
Philadelphia, PA
- Shares complex information related to areas of expertise and/or to gain acceptance of new or enhanced business solutions. "Evangelizes" new ideas / solutions to gain acceptance from a wide range of audiences
- Develops business approaches and new or enhanced processes
- Experience with programming in one or more of the following: databases, scripting, object-oriented programming, and high-performance computing
- Experience with developing software to train learning algorithms on large datasets
- Perform innovative machine learning research and software development and work independently on complex tasking
- Effectively communicate results to both technical and non-technical audiences
- Design, participate in, and conduct research and evaluation projects on digital learning and assessment
- Articulate and use knowledge of trends in technology and education in collaborative consultations and research projects
Machine Learning Data Scientist
09/2010
-
08/2017
Philadelphia, PA
- Plan and track work packages under purview
- Understand and manage intercomponent dependencies within a work package and interwork package dependencies
- Validate that the requirements given are ready and full to be taken up by the Technical Lead and the team
- Identify gaps in requirements vs the envisaged high level scope and milestone (including NFRs, usability, user adoption and other implicit requirements)
- Identify key machine learning technologies and algorithms, and determine how they’ll impact ARM products and partners
- Learn about the oilfield domain
- Publish research papers, internal technical reports and patents, and present your work
- Competency in algorithm development and implementation
- PhD in CS Machine Learning or Distributed Systems
iXp Intern, Machine Learning Data Scientist
05/2005
-
07/2010
San Francisco, CA
- Guide the technical implementation of new data collections, visualizations and reports in answering research questions
- Establish a research program relevant to the goals of the research center and develop reputation as a thought leader in relevant areas
- Statistical Modeling Skills (SAS, SPSS, R)
- Strong NoSQL and SQL experience
- PhD in Computer Science, Applied Mathematics, Physics or Engineering
- Publications in major conferences and/or journals
- Great design and problem solving skills, with a strong bias for architecting for performance, scalability, usability, security, and reliability
- Experience in one or more of the commonly used parallel/distributed systems/technologies (Apache Hadoop, Apache Spark, MPI, CUDA, ...)
- Requirements Understanding: Understand high level requirements
Education
Huntington University
1999 - 2004
Science's Degree in Computer Science
Professional Skills
- Strong C++/Java skills (4+ years experience)
- Strong programming skills in one or more in the following: C++, Python, Java
- Experience with pattern recognition, predictive modeling and data mining skills
- Experience in development and implementation of machine learning software, preferably strong experience with Deep -Learning frameworks
- Experience with applied statistics skills, such as distributions, statistical testing and regression
- Strong oral, written, and interpersonal communication skills and an ability to work in a collaborative team setting
- Demonstrate project management skills necessary to lead research or development collaboration projects
How to write Learning Scientist Resume
Learning Scientist role is responsible for programming, java, modeling, design, reliability, reporting, finance, training, integration, database.
To write great resume for learning scientist job, your resume must include:
- Your contact information
- Work experience
- Education
- Skill listing
Contact Information For Learning Scientist Resume
The section contact information is important in your learning scientist resume. The recruiter has to be able to contact you ASAP if they like to offer you the job. This is why you need to provide your:
- First and last name
- Telephone number
Work Experience in Your Learning Scientist Resume
The section work experience is an essential part of your learning scientist resume. It’s the one thing the recruiter really cares about and pays the most attention to.
This section, however, is not just a list of your previous learning scientist responsibilities. It's meant to present you as a wholesome candidate by showcasing your relevant accomplishments and should be tailored specifically to the particular learning scientist position you're applying to.
The work experience section should be the detailed summary of your latest 3 or 4 positions.
Representative Learning Scientist resume experience can include:
- Strong communication skills & team management experience
- Excellent time management and organizational skills with the ability to handle multiple tasks and priorities
- Excellent data storytelling and interpersonal skills to both technical and non-technical audiences
- Development experience in Python with good command over respective data pipelining, matrix algebra and statistics libraries
- In conjunction with the R&D team, ensure that technical narratives are communicated effectively (especially to non-technical users)
- Knowledge of domain mapping, learning progressions, or other methods of skills analysis
Education on a Learning Scientist Resume
Make sure to make education a priority on your learning scientist resume. If you’ve been working for a few years and have a few solid positions to show, put your education after your learning scientist experience. For example, if you have a Ph.D in Neuroscience and a Master's in the same sphere, just list your Ph.D. Besides the doctorate, Master’s degrees go next, followed by Bachelor’s and finally, Associate’s degree.
Additional details to include:
- School you graduated from
- Major/ minor
- Year of graduation
- Location of school
These are the four additional pieces of information you should mention when listing your education on your resume.
Professional Skills in Learning Scientist Resume
When listing skills on your learning scientist resume, remember always to be honest about your level of ability. Include the Skills section after experience.
Present the most important skills in your resume, there's a list of typical learning scientist skills:
- Relevant work experience, including research experience working in industry or an academic lab
- Demonstrated experience communicating business implications of complex data relationships and results of statistical models to multiple business partners
- Demonstrated experience with statistical and modeling software tools, such as SAS or R
- Effectively work with a team of data scientists exchanging knowledge
- Programming experience with GPUs
- Experience with some aspect of learning technology (for example: gamification, social learning, micro learning, learning content tagging, etc.)
List of Typical Experience For a Learning Scientist Resume
1
Experience For Machine Learning Data Scientist Resume
- Programming experience in one or more of the following: Java, Scala, C/C++, Python
- Knowledge and experience using one or more of the following or similar machine learning software frameworks: CAFFE, Pytorch and Tensorflow
- Clearly communicate the learning strategy and plan for Microsoft’s next generation learning experiences related to your specific area of expertise
- Solid understanding of linear algebra, algorithms, machine learning, optimization, numerical methods
- Deep learning programming experience with Python/Tensorflow or similar library in a GPU environment
- Contribute to, and possibly lead (depending on experience), grant proposals and related efforts to attract funding
2
Experience For Machine Learning Research Scientist Resume
- A PhD in Machine Learning, Natural Language Processing, Computer Vision or equivalent experience
- Experience with statistical modeling and machine learning
- Experience in Natural Language Processing (NLP) and Natural Language Understanding (NLU)
- Experience in working with large data sets using Hadoop, Hive, Pig
- Partner with teams across Microsoft to align our next generation learning experiences with our company strategy
- Development experience in a scripting language (PHP, Python, Perl, etc.)
- Experience with data preparation, rationalization, and processing on big data
- Solid background in machine learning and/or statistics, publication history
- Reinforcement learning experience
3
Experience For Artificial Intelligence & Machine Learning Research Scientist Resume
- Post-graduate research experience including
- Experience with training models on time series data
- Experience in the field of Data Science and Statistical Research, Data Mining and Data Analysis
- Experience using query languages such as SQL
- Demonstrated ability in the application of Machine Learning to real-world industrial settings with large scale data
- Relevant data science experience
- Lead projects and develop strong collaboration with other team members and across the firm
- Ph.D. in Computer Science, related technical field or equivalent practical experience
4
Experience For Deep Learning Research Scientist Resume
- Experience with Linux system administration and container management with Docker
- Experience with Tableau
- Experience with computer vision libraries like OpenCV
- Experience with statistical modeling/machine learning
- Analyzing, summarizing and presenting results to functional teams and decision makers
- Identifying and establishing relationships with internal/external partners
- Tuning and optimization of sequential deep learning models
- Working knowledge of STL & Boost
- BA/BS in a field that emphasizes analyzing, displaying, or reporting on data (e.g., computer science, math, engineering, economics, statistics, psychology)
5
Experience For Deep Learning Scientist Resume
- Train machine learning and deep learning models on a computing cluster to perform visual recognition tasks, such as segmentation and detection
- Contribute to building deep learning models solving our customers’ toughest problems
- Develop plans for data collection and analyses for future machine learning and natural language processing capabilities
- Optimize deep neural networks and the associated preprocessing/postprocessing code to run efficiently on an embedded device
- Execute complex machine learning and deep learning projects that have a significant impact on Bosch global business
6
Experience For Machine Learning / Data Scientist Strategist Resume
- Provide technical leadership, driving and shaping research directions in Medicinal Sciences and broader R&D
- Hands on participation in systems research in deep learning and HPC platforms including hardware and software components
- Collaborate with the AMD research and engineering to optimize machine learning frameworks and applications
- Build deep learning models solving our customers’ toughest problems
- Build Machine Learning models to solve real problems working with real data
- BS or MS in computer science, electrical engineering, computer engineering or related fields
- Hands-on deep learning application (Tensorflow, Torch, Caffe or Theano) in a corporate setting
- Theoretical and practical knowledge in deep learning, machine learning and big data
- +10 years of PhD in CS Machine Learning, Data Management or Distributed Systems
7
Experience For Automated Driving Research Scientist Machine Perception & Learning Resume
- Work on cutting-edge research projects in applied AI and Machine Learning in the newly established Applied AI Research Lab with AI Products Group at Intel Nervana
- Experience programming in C++, Python or Java
- Develop and apply Machine Learning solutions to address real-world automotive and mobility challenges
- Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results
- Develop and execute proofs of concept and A/B tests that allow us to deliver the most impactful learning approaches
- Provide subject matter expertise to Microsoft on the latest/greatest approaches to your specific area of learning technology expertise
- Embed data collection and feedback mechanisms throughout our learning solutions to generate data-driven, actionable insights
- Develops the highly- complex or industry- approaches to drive the development of broad reaching strategies
- Share knowledge by clearly articulating results and ideas to customers, managers, and key decision makers
8
Experience For Data Science & Machine Learning Research Scientist Resume
- Record of publications in the area of machine learning or data analytics
- Thirst for knowledge and always willing to learn and assist colleagues
- Familiarity with Government and industry working groups and communities of practice
- Familiarity with distributed learning technologies (e.g., xAPI)
- Knowledge of machine learning algorithms and principles
- Broad knowledge of machine learning algorithms and principles
- Ph.D. in Computational Linguistics, Engineering, Statistics or related field
- Comfortable working in a fast-paced, highly collaborative, dynamic work environment
9
Experience For Senior Deep Learning Scientist Speech Resume
- Highly proficient with analytical/predictive modeling software. (Python/R/or similar)
- Hands-on text analytics in a corporate setting
- Comfortable working with Unix and Linux
- Analyzes source data and data flows, working with structured and unstructured data
- Manipulates high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships and trends
- Applies machine learning technology to solve real-world automotive related problems
- Collaborates internally and externally to identify new and Client data sources and explore their potential use in developing actionable business insights
10
Experience For Research Scientist Digital Learning & Assessment Resume
- Working with very large datasets in distributed Linux/Unix environments
- Deep reinforcement learning
- Proficiency with Python, C++, etc. and at least one of the popular deep learning frameworks, able to write production quality code
- Knowledge of Total Learning Architecture (TLA)
- A working knowledge of DNNs
- A working knowledge of Spark
- Knowledge of Machine Learning theory
- Areas of research include, but not limited to
- Apply and develop appropriate statistical, machine learning, and/or deep learning models and algorithms to classify structured or unstructured data into safety hazard categories or other classifications
List of Typical Skills For a Learning Scientist Resume
1
Skills For Machine Learning Data Scientist Resume
- Domain experience in developing and applying machine learning methods to one of the following areas: biology, chemistry, physics
- Experience in employing machine learning in a commercial setting – in collaboration with product development teams
- Programming experience including Python
- PhD in Machine Learning (preferably Deep Learning) with excellent publication record
- Experience with various machine learning and modeling techniques and parameters that affect their performance
2
Skills For Machine Learning Research Scientist Resume
- Experience with Data Science algorithms including sensitivity analysis, decision trees, clustering, regression analysis and Information Theory
- Experience building anomaly/outlier detection frameworks and performing time series analysis
- Masters' or PhD in a quantitative field and hands-on experience with Machine Learning/Deep Learning
- Experience with Machine Learning and Data APIs
- Experience in at least one of the following languages: Python, R, MATLAB, Java, C/C++/C#, SAS
- Experience with high-performance Deep Learning frameworks such as TensorFlow, PyTorch, Theano, Caffe, Caffe2, or MXNet
3
Skills For Artificial Intelligence & Machine Learning Research Scientist Resume
- Experience in learner-focused design and gamification learning technologies
- Experience in program management or product planning
- Experience building deep NN models for image classification, object detection and semantic segmentation
- Hands-on experience in distributed training of deep architectures: multi-GPU, multi-node, synchronous and asynchronous
- Programming experience, in particular Python
- Experience in development and implementation of state-of-the art Deep Learning technologies
4
Skills For Deep Learning Research Scientist Resume
- Experience in Python, or another scripting language; command line usage, e.g., Bash
- Proven track record of achievements in language research and development for Automatic Speech Recognition or Natural Language Processing
- Strong grasp of computer science principles, including data structures
- Experience with machine learning models, statistics
- Experience with deep learning frameworks (TensorFlow, PyTorch, CNTK, etc.)
- Experience with innovation accelerators
- Motivation and experience to define personal research roadmap
- Experience with distributed systems and frameworks
- Strong publication record and/or portfolio of open-source software
5
Skills For Deep Learning Scientist Resume
- Experience with various data analysis and visualization tools
- Experience in algorithms and data structures
- Experience with the data and platform aspects of the projects
- Demonstrated ability in the application of machine learning in real-world industrial settings with large scale data
- Experience with deep learning frameworks such as TensorFlow, Caffe, Caffe2, PyTorch, or MxNet
- Proven, relevant research with publications in relevant journals
6
Skills For Machine Learning / Data Scientist Strategist Resume
- Experience with a deep learning framework (e.g., TensorFlow, PyTorch, Keras, CNTK, etc.) is helpful
- Work experience in a relevant field
- Recent experience with C++ or Java
- A track record of relevant research demonstrated by publications in NAACL, ACL, CVPR, ECCV, ICML, NIPS, ICLR, IJCAI, SIGIR, AAAI, KDD, or WWW
- Experience with NLP is also very useful
- Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc
- Track record in integrating machine learning with real-time computing (including mobile apps and front-end systems)
7
Skills For Automated Driving Research Scientist Machine Perception & Learning Resume
- Track record in integrating deep learning with real-time computing (including mobile apps and front-end systems)
- Perform analysis using industry leading text mining, data mining, and analytical tools and open source software
- Broad knowledge of machine learning (including topics such as graph theory, hierarchical modeling, and Bayesian inference)
- Participate in all phases of a product development, from product definition and architecture and design, through implementation, debugging, testing and support
- Ph.D in machine learning/deep learning or related fields
- Proficient in machine learning and deep learning algorithms
- Familiar with popular deep learning models and proficient at least one open source deep learning framework
- Builds complex programs for running mathematical or statistical tests on data and for understanding complex relationships across attributes
8
Skills For Data Science & Machine Learning Research Scientist Resume
- Explores data using a variety of advanced statistical (e.g., data mining) techniques to answer business questions or guide future model development
- Builds complex programs for running statistical tests on data and for understanding correlation of various attribute
- Expertise in deep learning model, machine learning algorithm
- Ph.D in Computer science, electrical and computer engineering or related field with focus on deep learning and feature discovery
- Track record of diving into data to discover hidden patterns and of conducting error/deviation analysis
- A postgraduate (MSc/PhD/Post-doc) qualification in a numeric discipline such as Statistics, Machine Learning, Computer Science, Signal Processing etc
- Use existing deep / machine learning libraries (e.g., TensorFlow, Torch, Theano, Caffe, and scikit-learn)
9
Skills For Senior Deep Learning Scientist Speech Resume
- Publish papers and attend conferences in leading venues representing Bloomberg
- State of the art deep learning (e.g., hyper-parameter tuning, sequence-to-sequence methods, word/entity embeddings, CNNs, etc.)
- Deep Reinforcement Learning and Unsupervised Learning / Generative models
- Deep Reinforcement Learning, Unsupervised Learning, and Generative models
- Test performance of machine learning and deep learning models
- Active development in machine learning applications using recognized software frameworks
10
Skills For Research Scientist Digital Learning & Assessment Resume
- Familiar with the recent advances in deep leaning research community
- Agent-based modeling / Symbolic artificial intelligence
- Application of AI / ML for autonomous vehicle perception, planning and behavior systems
- Prepares testing scenarios and tests model performance
- Gain in-depth understanding of Humana’s data assets
- Familiar with at least one deep learning framework, e.g. Tensorflow, MXNet, Caffe, etc
- Knowledge of Cloud environments - like Azure and Google Cloud - within the context of Machine Learning and data
- PhD in a quantitative field such as Computer Science, Computer Engineering, Statistics, Economics, Mathematics, or Physics
- Comfortable working in a fast-paced and innovative environment where problems are not always well-defined
List of Typical Responsibilities For a Learning Scientist Resume
1
Responsibilities For Machine Learning Data Scientist Resume
- Collaborate with internal stakeholders (Safety, Engineering, R&D, Quality and IT) to understand business challenges and develop analytical solutions to optimize business processes
- Experience working with computer science fundamentals (algorithms, data structures)
- Work experience with machine learning and statistics, publication history
- Experience with a deep learning framework (e.g., TensorFlow, PyTorch, Keras, CNTK, etc.)
- Model deployment and scaling experience
- Experience with one or more of the following: Torch, TensorFlow, Theano, Caffe
- Demonstrated expertise in high performance computing software development
- Experience in data science
2
Responsibilities For Machine Learning Research Scientist Resume
- Experience with R&D and innovation type activities
- Experience with R and Python or Java
- Experience with common data science toolkits, such as Weka, Anaconda or others
- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase or others
- Demonstrated ability to architect, plan and deliver solutions to market
- Experience with Python (Scikit-learn, Pandas, Numpy)
- Highly experienced with the information technology aspects of data collection, organization, and integration
3
Responsibilities For Artificial Intelligence & Machine Learning Research Scientist Resume
- Experience with NLP
- Has proposed methods for improving learning under specific conditions and assessed these hypotheses
- Collect sample data using statistical techniques
- Provide infrastructure requirements to IT to run deep learning models
- Leads adoption of emerging technology products tools and analytic techniques
- Data Modeling - Advanced
- Machine Learning - Expert
- Integrates machine learning techniques for continuous improvement of results
- Leads personalization efforts by incorporating customer models and site data
4
Responsibilities For Deep Learning Research Scientist Resume
- Analyze source data and data flows, working with both structured and unstructured data
- Manipulate high-volume, high-dimensional data from a variety of sources to identify value-generating patterns, anomalies, relationships, and trends
- Develop advanced training content for briefings, seminars, workshops, and tutorials, and assist with its delivery
- Provide advanced user support for topics involving AI, data, and data analytics
- Enrol in, and complete an M.S./Ph.D. course of study at a leading Singapore university under the Industrial PostGraduate Program (IPP)
- Have the chance to work with the richest data sets available in the world addressing real-world problems
- Contribute to encapsulation of deep learning models in scalable cloud services
- Execute work related to Total Learning Architecture
5
Responsibilities For Deep Learning Scientist Resume
- Recurrent Neural Networks, Sequence Learning and Sequence Analysis (and NLG)
- Serve and point-of-contact, determining metrics and methods
- Have worked with compiled and scripting languages
- Comfortable working in a fast paced and innovative environment where problems are not always well-defined
- Understand vehicle safety data and how to use it appropriately in data analysis
- Present analytical approaches and results to internal audiences by synthesizing complex data and concepts into easy-to comprehend, comprehensive, and cohesive presentations
- Apply your knowledge in quantitative analysis, and the presentation of data to see beyond the numbers and help inform, influence, support, and execute our business decisions
- Design and build systems that solve problems involving text and time series data
6
Responsibilities For Machine Learning / Data Scientist Strategist Resume
- Publish in leading academic venues
- Study and analyze problems, propose solutions and design experiments
- Build novel prediction models
- Write, test and maintain C++ and Python code
- Designs and develops Advanced Analytics Projects through business and analytical problem framing, data acquisition and creation, model approach definition, model building and solution deployment
7
Responsibilities For Automated Driving Research Scientist Machine Perception & Learning Resume
- Provides thought leadership for Advanced Analytics Projects
- Directs Integration of Advanced Analytics Models
- Artificial Intelligence – Advanced
- UNIX Shell - Advanced
- Python or R - Expert
- Collaborate with Product Development experts to understand their requirements and overall business needs
8
Responsibilities For Data Science & Machine Learning Research Scientist Resume
- Communicate and present model insights to business customers and executives
- Engage, develop foster and lead partnerships to advance research efforts across cross-functional projects
- Design scientific solutions for mining large data sets, and employing cutting edge techniques to develop scalable prototypes with transformational potential and value
- For senior roles, lead, inspire and mentor junior scientists and research assistants (interns)
- Create the next set of methodologies for data classification and error detection
- Leverage big-data technology to design, prototype, develop and optimize production algorithms
9
Responsibilities For Senior Deep Learning Scientist Speech Resume
- Partner with key stakeholders to understand their needs and build new solutions
- Defining, deploying and institutionalizing functional area research approaches and related knowledge basis. Forecasting and assessing industry trends and their impact on designs and methods of the specified functional area
- Establishing research guidelines, best practices and standards
- Interprets highly complex results and analyzes trends
- Collaborate with product, engineering, and marketing teams across many Bosch business domains (automotive, industrial, internet of things) to translate business needs into technical solutions
- Contribute to Bosch's patent portfolio
10
Responsibilities For Research Scientist Digital Learning & Assessment Resume
- Drive projects as the principle point-of-contact, with the ability to determine and elaborate on suitable metrics as well as methods
- Write, test, and maintain production-quality code (mainly C++)
- Work with stakeholders to refine requirements and communicate progress, and Translate discussions into solutions
- Develop & Deploy models to production
- Participate in internal and external forums
- Leverage the scale of Pfizer proprietary data, applications, and GPU-compute infrastructure to develop custom, scalable machine learning methods for challenging problems in the life sciences
- Clearly communicate the value and efficiency of new methods, technologies, and research in order to advance adoption and awareness throughout R&D
- Work closely with other teams within Computational Sciences as well as internal partners to transfer methods and technologies to new intelligent software and systems
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