You will be responsible for leading the vision, design and development of scalable Machine Learning (ML) solutions for Danaher’s IoT and Analytics (ML) initiatives.
You will work with other Data Scientists, Data Engineers, ML engineers, and cloud Engineers and business groups and lead the development of innovative ML models for Danaher’s big data from health sciences, medical diagnostics, industrial and environmental sciences markets.
You will use your Agile experience to work collaboratively with Product Managers / Owners in geographically distributed teams.
Understand business challenges and propose new modeling and algorithmic solutions that leverages the latest in statistical and machine learning techniques
Study new data sources and find insights / correlation to investigate how data can be used to solve new business challenges.
Create prototypes with data sets and provide guidance on leveraging and combining new data sources for new business insights
Apply statistical analysis and modeling techniques on small and large datasets to solve specific business problems in diverse industrial domains
Provide strategic leadership in selection of platform, tools, techniques and processes in the practice of Data Science discipline
Work collaboratively with Product Owners / Product Managers from other business units and / or customers to translate business requirements in to technical requirements that can be answered with statistical and machine learning techniques.
Guide and work with engineers and domain owners to produce the required data if not available
Provide mentorship to other Data Scientists in the team
Own and drive contemporary best practices in applying and deploying data science at scale
Advanced degree, PhD preferred, in Engineering, Science, Mathematics, or related
7+ years and expert knowledge of statistical programming languages such as R, Python, and SQL
7+ years and expert knowledge of probability, statistics and machine learning theory including experience in : Clustering, Decision Trees, Logistic Regression, Dimensionality Reduction, Random Forests, and Neural Networks for prediction and recommendations
Must have delivered data science components as part of a commercial solution at scale
5-7+ years’ experience in at least one of the following specific areas of machine learning :
Building production-ready image or video analysis models using Deep Learning techniques such as CNN and RNN
Leveraging tools such as TensorFlow or Theano
Building operations analytics models, including demand forecasting, inventory optimization in manufacturing or related industries
Building IoT analytics models, including failure diagnosis and failure prediction
Executing customer advanced analytics, including marketing mix analysis, segmentation, retention modeling, targeted marketing, basket analysis, and next product recommendation
Executing data science in the fields of life sciences, medical diagnosis, and biostatistics
Readiness to work with engineering teams to develop a prototypes of software products leveraging exploratory data analytics
Consultative experience providing technology and solution consultation to customers / clients
Experience and knowledge of contemporary Machine Learning and / or Analytical platforms and tools, especially from Amazon, Microsoft or ML Studios from others
Expert knowledge of data visualization, using tools such as Tableau or PowerBI
Experience developing and deploying on Amazon AWS and / or Microsoft Azure IaaS / PaaS cloud infrastructure
Experience working with distributed data storage and computing, including Hadoop, Spark, Cassandra, and so forth
Experience working with traditional databases, such as MS SQL, Teradata, MySQL, and Postgres
Expert knowledge of Experimental Design and Statistical Decision Theory
Agile mindset to jump in to a diverse set of projects
Ability to summarize results from analysis to a diverse set of audiences with varying background and technical skills
Willingness to travel up to 40% required