Interdisciplinary senior scientist with 13 plus years of quantitative research and commercial experience. Expert in areas of automation, optimisation, parallelisation, advanced model development and with a proven track record in supporting technological growth of top tier organisations in several market areas.

Director @ • Developed a distributed streaming process for real-time web API's data cleaning, mining and analytics (Apache Storm, Java). • Developed an object-oriented (Python), stochastic virtual reality simulator of the consumer eco-system to generate high volume data streams in a custom/parametric fashion. The simulator is being used for development, testing and optimization of Big Data bespoke solutions. • Developed tools for automation of data extracts for visual analytics (Tableau) using relational and distributed data sets (SQL Oracle, noSQL Cassandra). The automated dashboards provide analytics to thousands of commercial customers on a global scale. • Developed automated processes for relational (SQL Oracle) and distributed (noSQL Cassandra) data warehousing, migration and cross-databases quality control, mining from several sources including DB's, endpoints and web API's (Python,Java). From June 2015 to Present (7 months) Big Data Scientist @ • Implemented a Mutual Information algorithm (Python) in Spark for correlation analysis of large categorical and mixed alphanumerical datasets. The implementation allows for statistical preprocessing aimed at reducing historical data width, which in turn may improve performance of machine learning algorithms. • Set-up a big data Spark/HDFS (Hadoop) cluster on the company's cloud servers. • Developed object-oriented modules for automated data pre-processing, cleaning and reporting. The modules are being applied to support standardisation of business customers data mining practices. From March 2015 to June 2015 (4 months) Big Data Science Research Fellow @ • Implemented a stochastic pattern recognition algorithm (fully non-naïve Bayesian classifier for advanced frequency analysis) for Big Data predictive analytics in Spark (Python, PySpark, Pig, Hive). • Tested the implementation in a cloud Spark/Hadoop cluster (128CPU’s, 1.2Tb RAM) on Amazon AWS EC2. • Experience with the MapReduce framework and its Spark and Hadoop implementation strategies. • Agile teamwork experience in solving Data Science problems using a variety of machine learning algorithms and libraries, i.e. scikit-learn, Mahout, and visualisation and analysis tools, e.g. Pandas, d3.js. From October 2014 to February 2015 (5 months) Technology Expert @ • Defined strategies for exploitation and numerical methods for the virtual design cycle at Airbus (UK and FR), which have been fully integrated saving an estimated £4M yearly in testing. • Supported knowledge transfer activities through sharing and implementation of best modelling practices across the Airbus industrial and research network. • Defined standards for down-selection of materials for safety-critical structural applications and developed automation techniques for analysis of large impact data sets as requested by Rolls Royce plc. From April 2008 to October 2014 (6 years 7 months) London, United KingdomResearch Associate @ • Composite structures design optimization using machine learning (Genetic Programming) and High Performance Computing (UNIX scripting, cloud computing) and set-up of a virtual design automated platform (LS-INGRID, LS-DYNA, LS-OPT). Major outcomes include the design of an innovative hybrid composite shield with 20% plus weight improvement and cost-savings compared to the industry standard solution. • Research collaborations with Rolls Royce plc (UK), Dowty Propellers (UK), Airbus (UK, FR), BAE Systems (UK), DSM Dyneema (NL), Honeywell (UK), Kuraray Vectran (USA), DSTL (UK). • Detailed understanding of the mechanisms of fracture and damage progression in composite structures under quasi-static and dynamic loadings through experimental, analytical and numerical modelling activities. Major results include a one-parameter physics-based formulation for predicting 3D strain-rate effects and hardening in UD composites; an anisotropic EoS formulation for shock analysis; a mesh-size objective, energy-based formulation for composites impact damage analysis; a visco-plasticity based approach for homogenised modelling of 3D composites; an anisotropic failure and damage formulation for impact analysis of light-weight, resin-starved and highly compliant shield systems. • FE, SPH, ALE material modelling (3D and 2D) with LS-DYNA, ABAQUS, ANSYS, NASTRAN using custom developed coupled formulations of general applicability (quasi-static up to shock loading conditions) for virtual design of large-scale composite aero structures. • Destructive and non-destructive testing of materials using standard and custom-designed (Pro/Engineer, Creo) equipment, i.e. implementation of a gas-gun and a mini-Hopkinson pressure bar in the department. • Developed, implemented and optimised novel solutions for composites manufacturing (RIFT, VARTM) achieving higher surface finish quality at a reduced cost for wavy composite architectures. • Tutored, trained and developed >10 UG and Ph.D. students. From April 2007 to October 2014 (7 years 7 months) Founder, Strategist @ • Led a team of eight professionals in business, IT, graphics design and international law. • Supervision of two projects at Imperial College London, Department of Computing: 1. “Scalable front end development”. 2. “Development of NoSQL solutions for management of data structures”. • Code development in CSS/JS/PHP/MySQL. • Part-time teambuilding and agile software development experience within a startup environment. From January 2013 to January 2014 (1 year 1 month) London, United KingdomLecturer in Finite Element Analysis @ The course included mechanics, mathematics and computational engineering. It involved the preparation and delivery of lectures, supervision of laboratory classes and supervision of design work. From September 2008 to November 2008 (3 months) Assistant Lecturer in Structural Design @ Support to the students in using the PCT framework for the modelling (ProEng) and analysis (ProMechanica) of critical aerospace components. From September 2004 to December 2007 (3 years 4 months)

PhD, Aeronautics, Engineering @ Imperial College London From 2004 to 2007 Laurea (MSc equivalent), Aerospace Engineering @ Politecnico di Torino From 1998 to 2004 Lucio Raimondo is skilled in: Fortran, Aerospace, Finite Element Analysis, Composites, Simulations, R&D, Numerical Simulation, Python, Numerical Analysis, CFD, Abaqus, LaTeX, Mathematical Modeling, Experimentation, Aerodynamics