Become A Senior Data Scientist

* We are looking for an experienced Senior Data Scientist Individual Contributor (IC) to play a lead role in our Supply Chain Engineering team to create advanced statistical models and analyze data to provide actionable insights and proactive measurements of the Supply Chain business.
* Responsibilities will include:
* Creating analytical models, performing analysis on data to identify trends, patterns, correlations, and providing insights from data to customers and business.
* Develop a good understanding of Microsoft’s cloud operations, problems and challenges, and provide insights and guidance to stakeholders through your modeling and analysis work.
* Design and implementation of machine learning and data science models in the Supply chain systems.
* Guide and coach junior member in the team to generate the right insights from the data

* Extraction and analysis of large healthcare claims data using SAS, SQL, R, Teradata, Hadoop, etc.
* Opportunity analysis including descriptive and multivariate statistics to identify patterns in the data
* Matched case-control studies and/or randomized control trials for determining the effectiveness of health program services and solutions
* Creation of actionable insights and recommendations for business leaders
* Presentation of results and recommendations to non-technical business partners and stakeholders to drive the decision-making process
* Partner closely with the business to ensure a cohesive understanding of our business strategy

* Selectingand transformingfeatures, building and optimizing classifiers using machine learning techniques
* Integrating data from multiple sources including third party sources.
* Data mining using state-of-the-art methods
* Enhancing data collection procedures to include information that is relevant for building analytic systems
* Frequent meeting/communication with clients to interpret their needs, plan/organize, and discuss progress and results
* Developing actionable quantitative marketing models in the areas of marketing effectiveness, ROI, pricing and optimization.
* Doing ad-hoc analysis and presenting results in a clear manner
* Creating automated anomaly detection systems and constant tracking of its performance
* Adapting and enhancing machine learning techniques based on physical intuition about the domain
* Review, direct, guide, inspire the analytical work of more junior staff
* Here are some of** **the** **specific technologies we use:
* Spark(AWS EMR), AWS Lambda
* SparkStreaming and Batch
* Avro, Parquet
* Kafka
* MemSQL, Cassandra,HBase,MongoDB, RDBMS
* Caching Frameworks(ElasticCache)
* Elasticsearch, Beats, Logstash, Kibana
* Java, Scala, Go, Python, R
* Git,Maven, Gradle, Jenkins
* Rancher, Puppet, Docker, Ansible, Kubernetes
* Linux
* Hadoop (HDFS, YARN, ZooKeeper, Hive), Presto

* Excellent leadership and communication skills, to influence and lead teams and to evangelize data science across the organization
* Proven leadership experience in the domain of Data Science
* Having a wide-latitude in determining objectives and approaches to solution development on mission critical assignments
* Going beyond established analytical thinking and problem-solving by applying creativity to unconventional concepts and out-of-the-box solutions
* Be part of a dynamic and cohesive team of highly trained and successful researchers
* Independence in the shaping and development of projects
* Ability to quickly understand patterns within large quantity of data and to reference key characteristics using visualization techniques
* Demonstrating strong programming skills in large-scale data analysis using Java, R, Python or related software
* Leveraging strong math skills and statistical knowledge to advanced data mining and data analysis activities related to next generation Cloud technologies 
* As an insight incubator, works autonomously or leads teams to generate or shape new and highly critical business propositions that exploit and monetize big data research
* Provides consultative guidance across Intuit's businesses on how best to utilize data for business decision-making, and to build the organization mind-set and capabilities needed to fully exploit this data as an asset
* Works with business planners to propose innovative products and services that fully utilize the power of big data, or that indicate the need for new data platforms and associated product/service functionality
* Sets self-initiated research objectives and exercises a wide latitude of discretionary judgment in exploring advances in artificial intelligence and applying innovative machine learning techniques to Intuit's data capturing and mining business strategy
* Collaborates with infrastructure architects in assessing and addressing the requirements for more automated, streamlined systems and for the data governance required for agile and responsive data manipulation
* Introduces industry-leading or academic-based ideas, research, and insights required by Intuit  leadership to solve complex questions or fuel new business opportunities
* Acts as an advisor in overseeing and mentoring the work of colleagues towards the building of a vibrant practice community
* Qualifications
* MS  in Engineering Mathematics, Statistics, Theoretical/Computational Physics, or related field
* Solid knowledge of statistical techniques is required
* years as either a lead in a data science role or in a management position in data science
* Strong communication skills and proven experience as an influencer at executive level
* Hands-on programming experience with one or more of the following: Java, Python, R, or related languages
* years’ experience manipulating large datasets and using databases (e.g.
* SAS, R, SQL, S-Plus, etc.)
* years’ experience with a general-purpose programming language (e.g.
* C, Java, Python, etc.)
* Familiarity with basic principles of distributed computing and/or distributed databases (Hadoop, NoSQL, etc.)
* Demonstrable ability to quickly understand new concepts---all the way down to the theorems—and to come out with original solutions to mathematical issues
* Strongly Preferred:
* PhD  in Engineering Mathematics, Statistics, Theoretical/Computational Physics, or related field
* Proven experience with Machine Learning techniques, especially on large scale datasets
* Proven experience with Hadoop and related programming environments (Hive,Pig,etc)
* Demonstrable skills in creative-problem-solving of complex and advanced technical subject matter
* Strong interpersonal and communication skills in order to effectively contribute to technical teams and make presentations to a variety of technical and business personnel
* EOE AA

* Provide scientific guidance on the application of Real World Evidence and observational research data to support pharmaceutical development problems
* Support Pharmacovigilance teams and Epidemiologists extract value from large observational research data
* Support technical teams provide access to analytical tools and develop visual analytics to enable self-serving applications for end customers
* Provide clear technical input, options, and direction to strategic decisions on Real World Evidence platform and capability build
* Provide strategic decisions on AstraZeneca Medical Evidence and Observational Research external collaborations in the US and other markets
* Provide technical input, options and directions to strategic decisions made by AstraZeneca observational study teams on study design, data partner selection and best practices in Real World Evidence data utilization
* Assist in building a capability that becomes a source of sustained competitive advantage for AstraZeneca/MedImmune in identifying, acquiring, integrating and mining diverse Real World Evidence data from multiple geographic and healthcare system sources to support evidence generation and real-world studies
* Assist in the delivery of analytics and the build of analytics pieces as part of an Real World Evidence strategy
* Evaluate and assess strengths and weaknesses of external Real World Evidence data sources via interrogation, and potential partners for advancing the data strategy for a given therapeutic area
* Maintain a strong insight into the capabilities of potential external partners in Real World Evidence, especially for US and emerging markets