qualifications.txt

	Degree in statistics, computer science, engineering or related quantitative field. 
	2 - 4 years of experience in an analytical role supporting business functions. 
	Knowledgeable advanced machine learning and statistical techniques including boosting, bagging, decision trees, regression, clustering, time series analysis etc.. 
	Some knowledge of deep learning models such as RNN, CNN etc.. 
	Experienced developing and maintaining models. 
	Advanced in Python or R, SQL and experienced in querying databases. 
	Experienced with AWS platforms. 
	3+ years of experience in applying data science techniques to drive technical product development and decision-making
	Strong technical background in computer science, statistics, math, information science, or another quantitative field
	Fluency in at least one modern language useful for data processing (e.g. Python, Scala)
	Proficiency with relational data modeling and SQL
	Expertise in statistical methods and experimental design and analysis
	Familiarity with distributed data processing systems (e.g. Spark, Redshift)
	Background in advanced statistical modeling (e.g. GLM, mixed effects) and/or machine learning
	Experience collaborating with teammates in other locations
	You are passionate about breaking down and understanding complex systems. 
	You are a strong critical thinker who thrives working with both technical and non-technical people. 
	You aren’t afraid of messy data, and excel at structuring and building analytical systems. 
	You know how to get things done in a modern data science stack - you have strong SQL skills, experience with data wrangling and script writing (we primarily use Python/pandas) and an appreciation for beautiful data visualization (we’ve mostly been using D3, Seaborn and Looker). 
	You see data science as a powerful tool to get things done rather than as an end in itself. 
	You get excited about taking ownership of problems and solving them in a fast-paced and scrappy environment.
	2+ years of relevant experience in Data Science 
	MS in Math, Statistics, Computer Science, Physics, Bioinformatics or another quantitative field 
	Customer facing experience and excellent presentation and communication skill 
	Programming skills that allow you to be self-sufficient in handling data (Python, SQL, Scala, Java) 
	Experience with statistical tools or packages (R / RapidMiner / Scikit)
	PhD in Computer Science, Applied Mathematics, or similar computational field 
	Extensive experience prototyping, refining and deploying predictive models and machine learning & AI, neural networks 
	Experience with frameworks such as TensorFlow, PyTorch, or similar 
	5+ years of software engineering experience 
	Proficiency with relational and document-based databases 
	4+ years working with cloud or distributed systems 
	Publication record in machine learning, artificial intelligence, or similar algorithmic fields
	Familiarity with document-based databases
	PhD in political science, sociology, mathematics, statistics or other related field or 4-5 years of experience performing data analysis work as described below
	Excellent general data science skills (data cleaning, munging, data visualization)
	Excellent Python or R skills
	Experience building machine learning models on large datasets
	Experience identifying appropriate statistical techniques and applying them to a variety of real-world datasets
	Strong problem-solving skills as well as the ability to manage several tasks/projects concurrently and prioritize work effectively
	Experience with databases and knowledge of SQL preferred
	Experience with Amazon Web Services, in particular applying analytics in that setting (desired not required)
	Interest in politics and/or educational policy
	6+ years of work and research experience in the machine learning field.
	A deep understanding of machine learning and interest in applying it at scale.
	Experience with data cleaning, preparation, and feature building and selection techniques.
	Experience working with large data sets to solve problems.
	Familiarity with relational databases 
	Experience with Spark and/or Hadoop would be very helpful.
	Experience with deep learning library like TensorFlow and/or PyTorch is highly desirable.
	Experience with GPU Computing is highly advantageous.
	Prior hands-on experience with Python, Java, R, C/C++, Scala or F# and the ability to write reusable and efficient code to automate analyses and data processes.
	Effective communication, interpersonal and teamwork skills. 
	Ability to handle multiple concurrent projects while working independently and in teams.
	Ability to work in a fast-paced and deadline driven environment.
	MS or Ph.D. in Computer Science, Statistics, Computational Linguistics, Artificial Intelligence, Operations Research, Mathematics or related fields.
	Ph.D. in a relevant technical (machine learning, computer science, physics, mathematics, statistics, or related field), or 4+ years experience in a relevant role 
	Extensive experience solving analytical problems using quantitative approaches using machine learning methods 
	Track record of using advanced statistical methods, information retrieval, data mining techniques 
	Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources 
	A strong passion for empirical research and for answering hard questions with data 
	A flexible analytic approach that allows for results at varying levels of precision 
	Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner 
	Fluency with at least one scripting language such as Python 
	Familiarity with relational databases and SQL 
	Expert knowledge of an analysis tool such as R or Matlab 
	Experience working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, HBase, etc.)
	Ph.D. in Computer Science, Math, Statistics or Machine Learning 
	2+ years of work experience in machine learning and natural language processing required
	Extensive programming experience in Java, Scala or Python, ability to work on projects with minimal engineering support 
	Experience with Spark, Hadoop/MapReduce and machine learning frameworks 
	Ability to communicate complex quantitative results in a clear, precise and actionable manner 
	Self-motivation and an ability to handle multiple competing priorities in a fast-paced environment 
	Ability to work both independently and collaboratively within a team
	5+ years of hands-on experience building data products powered by machine learning and/or optimization algorithms in non-academic environments. 
	Ability to break down and understand complex business problems, define a solution and implement it using advanced quantitative methods. 
	Meaningful experience with and deep technical understanding of statistical analysis, machine learning (classification, regression, unsupervised, reinforced, etc.), predictive modeling, and optimization algorithms. 
	Strong programming skills with an emphasis on libraries for cleaning, exploring and visualizing data. 
	Strong oral and written communication skills, especially around analytical concepts and methods. 
	Strong work ethic and intellectual curiosity. 
	Masters or Doctoral degree in a quantitative field (e.g., mathematics, computer science, physics, economics, engineering, operations research, quantitative social science).
	Experience in Recommendation Systems, Bayesian Inference or NLP
	Bachelor's degree in a quantitative field (math, statistics, computer science, economics, physics). Graduate degree a plus 
	3+ years of analytical experience at a tech startup or finance firm 
	Proficiency with Python and the scientific Python suite (numpy, pandas, scikit-learn, matplotlib, Jupyter notebooks) 
	Proficiency with SQL 
	A solid foundation in statistics (probability distributions, maximum likelihood estimation) and undergraduate math (multivariable calculus, linear algebra) 
	Familiarity with deep learning (TensorFlow, Keras, or PyTorch) 
	An excellent teacher and storyteller 
	Bonus: familiarity with engineering tools (GitHub, Heroku, Docker)
	5-6 years experience working in an analytics or data-focused role, preferably within a smaller to medium-sized organization. 
	Relevant work experience owning marketing and/or behavioral analytics strategies, with an emphasis on having worked on analyses and models in the space yourself 
	Experience with predictive modeling (classification, regression, parameter tuning, feature selection, validation, performance reporting), preferably with multiple techniques 
	Proficiency with common data manipulation and modeling tools (SQL, Python, R, Tableau) 
	Bachelor’s degree in Finance, Mathematics (Economics) or a closely related quantitative field 
	You communicate clearly and take a user centric approach to creating analyses and models, i.e., you can weigh appropriately the need for accurate modeling with interpretable modeling. 
	You are quick with numbers and back-of-the-envelope calculations. 
	You have a good eye for model fitting and biases in the statistical context as well as in the application of the model 
	You are willing to work with programmers and other data scientists to constantly improve the integrity and automation of your work. 
	You are well organized and can handle many unrelated requests without losing track of them. 
	You can use software to organize your activities when needed. 
	You have exceptional written and verbal communications skills. 
	You are a hands-on problem solver who is comfortable with ambiguity and loves a fast-paced environment. 
	You have strong interpersonal skills and are capable of building relationships to drive success.
	3-5 years of academic or professional experience in a quantitative role 
	Experience translating business problems into data problems and solving them 
	Comfort turning ideas into code (bonus points for experience with Python or Scala) 
	Commitment to creating and sharing reproducible analysis 
	A passion for constantly learning and teaching others
	Streaming data (Reactive Extensions, Spark Streaming, Akka-streams, Kafka, RabbitMQ)
	AWS infrastructure (we use Redshift, S3, EMR, Kinesis, Lambda, and RDS)
	Building distributed software (especially on top of Spark, Hadoop, etc.) in a production environment
	Utilizing applied statistics or machine learning on large, complex, noisy datasets
	Scaling and turning statistical models into production-ready applications such as recommender systems
	Languages: Python for web services and product devlopment, R for analysis and prototyping 
	Datastores: MySQL, Redshift, Elasticsearch, Redis 
	Monitoring: Graphite/StatsD 
	Version control: Git
	2+ years of experience in an operational Data Science role.
	Demonstrable professional command of Machine Learning and Data Science toolsets such as Python (Numpy, Scipy, Pandas, Scikit-learn), R (dplyr, tidyverse, ggplot).
	M.Sc. or Ph.D in computer science, engineering, statistics, computational linguistics, or other quantitative field or relevant equivalent professional experience
	Understanding of and demonstrable experience using statistical principles to communicate results (experimental design, a/b testing and other frameworks).
	Ability to collaborate with Data Scientists and Data Engineers to propose, test, validate, evaluate, and deploy Machine Learning Models.
	Hands on experience using Apache Spark in a professional context
	Strong SQL skills
	Hands-on experience and understanding of Graph and/or search Databases (e.g. neo4j, elasticsearch) is a plus
	Healthcare experience and a basic understanding of clinical terms is a plus
	Experience building knowledge graphs and representations is a plus
	Ph.D. in a quantitative field (e.g. machine learning, statistics, physical science, or quantitative social science) -- or -- 
	M.S. in computer science or statistics plus two years of professional experience.
	Experience using real data to solve real problems is a must.
	The ideal candidate has experience working with data to develop innovative products in a business context.
	Expertise in statistical modeling, machine learning, and fluency in the related technical tools is a must. 
	Programming skills (we primarily use Python on the data science team).
	Excellent oral and written communication skills; comfort in a client-facing role.
	A track record in contributing to publications, presentations, external collaborations and service to the research community is a plus.
	2+ years experience of bringing data science products into production 
	Excellent communication and data visualization skills 
	Proficiency with Python 
	In-depth knowledge of machine learning and statistics 
	High proficiency with SQL and relational databases 
	Experience planning and executing A/B tests 
	A passion for learning 
	Experience with deep learning and related libraries such as tensorflow or pytorch 
	Experience with engineering data workflows using frameworks such as Airflow or Luigi 
	Knowledge of distributed computing and associated frameworks such as Hadoop, Spark, Hive, Presto, Impala or equivalent 
	A passion for building great products
	Obsessed with data; analytical and rigorous, with a thorough understanding of statistics and machine learning 
	Extraordinary communicator with demonstrated writing and editing skills. 
	Passionate about elegant visualization; you understand the importance of graphic techniques in communicating a quantitative idea effectively 
	Deep understanding of business concepts within strategy, operations, and marketing 
	Have a Masters Degree or PhD from a top-tier university (statistics, machine learning, physics, math, systems biology, or highly quantitative fields in social sciences), including 2+ years of graduate-level research experience (or the equivalent) 
	Have experience with predictive modeling and statistical analysis techniques in a business environment 
	Mastery in some or all of the following: SQL, Python, R, and Tableau
	Degree in statistics, mathematics, computer science, economics, or other quantitative field required; Graduate degree preferred 
	2-4 years of experience working with advanced analytic techniques in classification, regression, optimization and text analytics 
	Experience implementing machine learning algorithms (Random Forest, SVM, etc.) in production settings 
	Proficiency in either R or Python 
	Familiarity with data extraction across different database architectures 
	The ability and desire to identify and deploy novel solutions to business problems   Strong interpersonal & communication skills 
	Ability to maintain a fun, casual, professional and productive team atmosphere 
	Excellent communication skills with the ability to communicate in a courteous, tactful, and concise manner 
	Ability to work with a diverse team in a fast-paced environment 
	Enthusiasm and the ability to thrive in an atmosphere of constant change
	4+ years of experience performing data analysis; or 2+ years of experience performing data analysis and a Master's degree/PhD in statistics, math, physical sciences, or another quantitative discipline, economics, quantitative social sciences, political science
	Expertise working with SQL, a scripting language (Python, Scala, and/or R), and distributed computing (Spark)
	Advanced understanding of statistics, working knowledge of complex experimental design, causal and descriptive modeling
	Experience using common machine learning techniques
	Experience working with business partners to coordinate research objectives, manage a research plan, and present results
	Ability to initiate and drive projects to completion with minimal guidance
	Masters/PhD Degree preferred, in a quantitative field, and industry experience as a data scientist.
	Proven history of leading projects from start to finish and shipping quality code (Be prepared to show us something you've built.).
	Able to independently and fluently translate business needs to data problems
	Excellent capacity to communicate results and progress to non-technical and technical audiences.
	Strong research, analytical and problem-solving skills.
	Solid grasp of statistics and predictive modeling techniques.
	Strong programming skills in Python and familiarity with SQL, noSQL, and/or ElasticSearch
	MS in Computer Science, Statistics, Applied Mathematics, Physics, Engineering or a related field with 3+ years of experience 
	2+ years of professional programming work in Python, Scala, Java, or similar 
	Experience with Pandas, R, or other statistical modeling frameworks 
	An understanding of storing and querying data from Redshift, PostgreSQL, or similar 
	Passion to use all aspects of data science, programming, and technology to build the financial advisor of the future 
	Experience using machine learning to improve algorithmic systems 
	Experience with machine learning frameworks such as Apache Spark or Apache Hadoop/MapReduce
	2-5 years of experience applying descriptive statistics, machine learning, building predictive models and visualization to solve real-world problems 
	MSc or PhD in in statistics, mathematics, computer science or another quantitative field 
	Comfort communicating analytical findings to people of diverse backgrounds using statistical libraries and visualization tools in Python 
	Excellent programming skills in Python 
	Data querying capabilities using SQL 
	Ability to explain technical concepts in simple terms to business stakeholders 
	Strong skills and experience leveraging Python, R and SQL to produce production ready solutions 
	Expertise in quantitative analytics including machine learning, clustering, regression, and other approaches 
	Experience in a business analytical role a plus, preferably in commerce or consumer media
	Degree in computer science, statistics, engineering or other applicable quantitative discipline
	1+ years of experience doing quantitative analysis involving real world data
	BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field
	Proficient in Python and SQL
	Experience manipulating large data sets with the ability to transform real world data into appropriate shape to be used in modeling 
	Understanding of statistics (e.g., hypothesis testing, regression) and machine learning algorithms
	Comfortable building reproducible code to share while learning new technologies
	Ability to communicate the results of analyses with excellent presentation skills or visualization tools
	An analytical mind with strong statistical skills, a creative streak and appetite for staying current with research papers and conducting new studies that move the industry forward
	2 or more years of progressively complex related experience
	Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas
	Expertise in using R or Python to manipulate large data sets and develop statistical models
	Expertise in data management in an Hadoop environment, including use of Hive
	Excellent problem solving skills, critical thinking and conceptual thinking abilities
	Strong ability to communicate technical concepts and implications to business partners
	Some knowledge of health care industry preferred
	We do continuous deployment and we ship code 50-100 times every day
	The data stack is all in Python 3.6
	We use Node.js, Python and Scala for services
	Postgres for the database, Kubernetes, for deployment and devops
	AWS for infrastructure, leveraging EC2, S3, SWF, CloudFront, Route53, and much more
	Professional experience using advanced analysis to guide strategic decisions at the company level
	You know how to use the right tool for the job, whether that's a programming language (like R or Python) or just plain old SQL
	Experience working with statistics and supervised/unsupervised models
	Communication: you love to talk about your work and findings, and can clearly explain the details
	Familiarity with Amazon Web Services, Apache Spark, Tensorflow, etc
	Ability to move quickly by making smart assumptions
	Experience working with e-commerce marketplaces is a big plus
	A love for travel, especially the hotel part!
	Master’s degree preferred in statistics, Economics, Econometrics, Computer Science, Engineering, or Mathematics with a strong quantitative background
	At least 5 years previous work experience with strong understanding and proficiency of econometric (including focus on price elasticity) and time-series modeling techniques. Machine learning background a plus
	Understanding of modeling techniques and specifically logistic regression, linear regression, cluster analysis, CHAID, market basket analysis, etc.
	Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses
	Proficiency in Microsoft Office Suite, SQL and R and/or Python
	Exceptional troubleshooting skills and should thrive in high expectation scenario with many stakeholders
	Excellent verbal and written communication skills; ability to present complex information in an easy-to-understand manner with clear recommendations based on data insight
	Strongly motivated to be a player in a team which is constantly working to improve themselves through discovering new analytics techniques and software tools to improve the quality of our work
	3+ years in a data science or similar role in the marketing, finance, forensics or technology fields required. 
	Extensive knowledge of machine learning techniques such as k-NN, Naive Bayes, SVM, Decision Forests, Data Mining, Clustering, and Classification. 
	Proficiency in statistics such as distributions, predictive modeling, data validation, statistical testing, regression. 
	2+ years of experience in machine learning/ statistical languages and systems such as Python, Matlab, R, SAS. 
	Bachelor’s degree in Computer Science or related field, with a strong quantitative background. 
	Ability to develop and maintain good relations and communicate with people at all hierarchical levels. 
	Strong problem-solving skills. 
	Ability to reconcile technical and business perspectives. 
	Autonomy and entrepreneurship. 
	Strong team spirit. 
	Passion for Rockstar Games and our titles. 
	2+ years using SQL (or a SQL-like language) required, other programming experience highly preferred. 
	Experience with Vertica and Hadoop, an asset. 
	Graduate degree (MBA, MSc or Master’s, PHD), an asset. 
	Game industry experience strongly desired.
	Demonstrated ability to present data science results and recommendations to business and technical clients.
	Demonstrated delivery of machine learning techniques in real-time applications.
	Expertise in modern statistics/data science/machine learning.
	Expertise in a statistical programming language (we use Python and R internally) and data access tools (e.g. SQL).
	Experience with deep learning, NLP, Neural Networks, and/or Bayesian modeling.
	Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick effective solutions as appropriate.
	Graduate Degree in statistics or machine learning
	PhD, MS, or 3+ years experience in computer science, applied mathematics, or other quantitative/computational discipline. 
	2+ years experience with open source machine learning or statistical analysis tools. Familiarity with experimental design a plus. 
	2+ years coding experience, Python preferred. 
	Ability to communicate complex ideas in data science to relevant stakeholders. 
	Data engineering experience, including SQL and manipulating large structured or unstructured datasets for analysis. 
	Preferred: experience with building data products, either internal or consumer-facing. 
	Preferred: Experience working with unstructured data and Natural Language Processing
	Commitment to the The Times’ mission of delivering the world’s best and most reliable journalism. 
	Excellent analytical and problem-solving skills 
	Strong oral and written communication skills 
	A passion for empirical research and for answering hard questions with data. 
	Proven record of solving challenging problems in academia and/or industry. 
	Eagerness to collaborate with both technical and non-technical colleagues in editorial, product management, marketing, and executive leadership groups. 
	Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick effective solutions as appropriate. 
	Desire to join the world’s most important journalism company at a moment in history when the importance of learning from our data is transforming every aspect of the craft and practice of journalism.
	Degree in a quantitative field like statistics, economics, applied math, operations research or engineering. Advanced degrees are preferred 
	4+ years of industry experience in a data science or analytics role 
	Proficiency in SQL - able to write structured and efficient queries on large data sets 
	Experience in programming, especially with data science and visualization libraries in Python or R 
	Strong oral and written communication skills, and ability to collaborate with cross-functional partners to build the business
	You have 3-8+ years of professional industry experience performing quantitative analysis. 
	You are an expert in SQL and have some experience with an analytical programming language like R or Python. 
	Prior experience with finance is a plus.
	You have a deep understanding of customers and products. 
	You have a proven track record of using analysis to impact key business or product decisions.
	You are passionate about sharing your insights with others. 
	You have the ability to clearly and effectively communicate the results of complex analyses via presentations, interactive dashboards, and verbally.
	You studied math, finance or engineering at the graduate or undergraduate level and have a solid grasp of applied statistics. 
	Prior experience in software engineering, data engineering, consulting or research is a plus. 
	2-5 years of experience in a data analytics, consulting, or other quantitative role 
	Examples of relevant experience include: Funnel optimization, user segmentation, cohort analyses, time series analyses, regression models, etc. 
	Experience with analyzing both client side and server side tracking a plus 
	An ability to write very complex SQL queries. ETL experience a plus 
	Proficiency in one or more analytics & visualization tools (e.g. Chartio, Looker, Tableau) 
	A deep understanding of statistical analysis (e.g. hypothesis testing, experimentation, regressions) and familiarity with statistical packages, such as Matlab, R, SAS or Python 
	Strong business judgment. You've got the ability to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way 
	Self-starter attitude. You’re someone who can initiate and drive projects to completion with minimal guidance 
	Get-it-done mindset. You’re not afraid of long hours, able to handle stress well, humble and scrappy! 
	A degree in Math, Physics, Statistics, Economics, Computer Science, or other quantitative field
	Degree or higher in Mathematics, Statistics, Computer Science or other behavioral and/or equivalent quantitative science 
	A minimum of 3 years of work-related experience in a similar or equivalent role. 
	Coding knowledge and experience with several languages, preferably: C, C++ and Java, JavaScript. 
	Solid experience in statistical and data mining techniques, specifically: GLM/Regression, Random Forest, Boosting, Trees, text mining and social network analysis. 
	Proficient in querying databases and using statistical computer languages such as: R, Python and SLQ. 
	Proven experience using web services; for example: Redshift, S3, Spark and DigitalOcean. 
	Able to create and use advanced algorithms and statistics such as: regression, simulation, scenario analysis and neural networks. 
	Skilled in analyzing data from 3rd party providers such as: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon and Facebook Insights. 
	Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi and MySQL. 
	Able to visualize and present finding to stakeholders using the following tools: Periscope, Business Objects, D3 and ggplot. 
	Strong problem solving skills with an emphasis on product development. 
	Must have excellent communication skills – verbal and written.