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Nicolas ******** Head of Data And AI

Summary

Data Engineer with over a decade of experience in applied data science solutions, specialising in operations research, business process improvement, product optimisation, and risk modelling. Known for transforming operational data into actionable insights to support decision-making.

Expert in tailoring and implementing frameworks for extracting and validating performance metrics, with a focus on continuous improvement and clear ROI aligned with business strategy. Extensive experience in data manipulation and applied statistical methods.

Led teams of PhD data scientists, software engineers, and economists in cross-industry data science initiatives. Demonstrated track record in collaborating with C-level executives, evidenced by personal recommendations on LinkedIn for expertise in applying data science to scale businesses.

SKills

AI EthicsAlgorithm DevelopmentArtificial IntelligenceAWSAzureBusiness IntelligenceGITPredictive ModelingReinforcement LearningSQLTableau
AI ConsultantAI Software DeveloperAI Trainer/Annotation Specialist

Education

Graduated 2018 Masters of Electrical Power Generation, Transmission and Distribution Projects at Universidad Tecnologica Nacional
Graduated 2014 Bachelor (Honours) of Engineering - Industrial at Universidad de Belgrano

Experience

Jan 2023 - Present Head of Data and AI at Learning Nodes

Key Responsibilities:
– Developed a data-driven funnel framework to optimise UX in web navigation and product usage, integrating every on-screen item into a cohesive, measurable funnel strategy with clear ROI indicators to facilitate streamlined data analysis, predictive modelling, and A/B testing.
– Utilised agile methodologies for efficient data science model deployments, emphasising continuous integration/continuous delivery (CI/CD) and feature rollouts via a Kanban board. – Implemented a collaborative data strategy focusing on row granularity, enabling precise data budgeting and comprehensive performance metrics for inter-sector data flow.
– Managed a diverse technical stack including Python, SQL, Airflow, Power BI, Vector databases, AWS, Chainlit, FastAPI, and Flask to support scalable data science endeavours.
Achievements:
– Pioneered the concept of understanding ROI on data flow between business sectors, leading to more informed strategic decisions and enhanced cross-sector collaboration.
– Established foundational data processes that enhance the potential for building complex algorithms and analytical solutions.
– Integrated cutting-edge technologies, fostering an environment conducive to the development and deployment of advanced solutions, including potential recommendation engines.

Jun 2022 - Jan 2023 ICMEC AU at Head of Data

Key Responsibilities:
– Built and directed a high-level team of doctorate data scientists and software engineers to apply data science methodologies on distinct datasets from both the clear and dark web.
– Identified behavioural patterns resulting in digital signatures useful for typologies and integrated them into a system to recommend classifications based on similarities.
– Initiated the incorporation of Quality Assurance on reinforcement learning, enabling time-series dashboarding for feature importance determination, forecasting, and A/B testing on momentum features.
– Managed the implementation of an open-source CRM for the Child Protection Fund (CPF), defining its business processes, agile structure, and data governance.
Achievements:
– Successfully derived actionable digital signatures from complex web data that played a pivotal role in typology creation.
– Led foundational systems and processes to streamline reinforcement learning quality checks, significantly enhancing predictive modelling capabilities.
– Played a central role in optimising the Child Protection Fund (CPF) communication processes by implementing and refining the CRM, resulting in improved stakeholder engagement and streamlined proposal evaluations.
– Enabled management to identify and act upon synergies between CPF proposals through the design and execution of a benchmark model.

Mar 2021 - Jun 2022 Head of Data at Asplundh Tree Services

Key Responsibilities:
– Reengineered the vegetation management quoting process by integrating advanced data science methodologies, with a focus on understanding utility parameters like subcontractor involvement, material usage, fleet logistics, and vegetation patterns.
– Leveraged diverse analytic techniques, including machine learning, linear programming, and simulations such as Monte Carlo, to address various modelling needs in the data pipeline.
– Led a cross-functional team comprising a business analyst, data engineer, and platform engineer, and operated as the primary data scientist.
– Enhanced the in-house ERP tool by implementing quality assurance improvements, providing actionable insights on tool utilisation, identifying areas of deficiencies, and adapting the tool for optimal performance in Hawaii and New Zealand.
Achievements:
– Successfully redefined the vegetation management quoting strategy, resulting in the acquisition of a 120 million AUD contract with Essential Energy.
– Provided critical quality assurance upgrades to the in-house ERP tool, leading to more efficient implementations in Hawaii and New Zealand based on localised performance metrics.

Feb 2019 - Oct 2019 Senior Data Scientist at Iron Cloud Finance

Key Responsibilities:
– Utilised a range of statistical methods, including both supervised and unsupervised machine learning techniques, to extract and produce measurable value within the loan business process. – Provided consistent analytics and data support to various stakeholders using tools such as Python, metadata, and Power BI.
– Collaborated with the growth department to segment customers based on their payment behaviours.
– Supported the engagement team by supplying analytics that enabled them to evaluate the effectiveness of their strategies.
Achievements:
– Successfully optimised the call centre operations using the Monte Carlo simulation, resulting in a tangible 10-15% increase in solutions relative to the cost of operations.
– Delivered actionable insights to the growth team by segmenting customers into categories like those who extended payments without defaulting and those who remained reliable even after an initial payment default.
– Enhanced the engagement team’s strategies by providing them with detailed analytics to gauge the success of their initiatives.

Feb 2018 - Feb 2019 Data Scientist at Tensorcharts

Key Responsibilities:
– Conceived and executed a method for A/B testing strategies within a neural network model tailored for algorithmic trading, with a focus on identifying non-correlated features to enhance order flow trading signals.
– Collaborated within an Agile framework alongside an international team comprising mathematicians, traders, and software engineers.
– Developed real-time dashboards to evaluate signal performance and seamlessly incorporate fresh signals into a deep-learning ensemble.
Achievements:
– Successfully introduced a robust A/B testing methodology in the neural network model, leading to optimised algorithmic trading strategies through the use of non-correlated features.
– Spearheaded the creation of real-time analytical dashboards, streamlining the integration of new trading signals and facilitating improved decision-making.

Jan 2016 - Feb 2018 Fraud Investigator/ Data Mining Coordinator at Edenor SA

Key Responsibilities:
– Led a 50-member interdisciplinary team tasked with identifying fraud within the electrical distribution network of Argentina’s largest supplier.
– Leveraged Machine Learning techniques in conjunction with Operations Research on data procured from power meters to detect anomalies and potential fraudulent activities.
– Created and maintained dashboards that illustrated detailed electrical consumption patterns across the grid.
– Designed KPI dashboards and initiated training sessions to install a continuous improvement approach within the organisation, centred around consumption analytics.
– Supervised both in-house and third-party interdisciplinary resources across various levels, ensuring consistent benchmarking of continuous improvement control systems, which included overseeing backlogs, OKRs, dashboards, documentation, and training initiatives.
Achievements:
– Successfully implemented advanced data analytics and machine learning strategies that led to a reduction in fraud, hitting a 10-year low in a SOX-regulated enterprise.
– Fostered a data-driven culture, empowering the organisation to adopt a continuous improvement methodology rooted in comprehensive consumption analytics.

Jul 2014 - Dec 2015 Purchasing Role at Exiros

Key Responsibilities:
– Managed the auction process, including the orchestration of Frame Agreements for the Petroleum, Metallurgy, and Construction sectors.
– Worked on enhancing the competitiveness of the market to improve the quality of suppliers.
– Applied decision theory to analyse market information and formulated KPIs to monitor supplier performance.
– Strategically planned demand to reinforce negotiation leverage with suppliers.
Achievements:
– Successfully closed over 2000 auctions, with Frame Agreements amounting to over 4 million USD.
– Contributed to significant improvements in supplier quality across key industries.
– Optimised negotiation strategies, leveraging planned demand to secure favourable terms and conditions for the company.

Dec 2012 - Jun 2014 Tenaris at PMO Analyst

Key Responsibilities:
– Overhauled the budget control process from initiation to conclusion, embedding continuous improvement measures throughout the Project lifecycle.
– Implemented comprehensive Quality Assurance for key project phases, including Business Cases, Objectives and Scopes, Quoting, and Project Closures.
– Served as the primary point of contact for over 100 Project Leaders and 10 Directors from diverse departments worldwide, tailoring communication strategies to accommodate individual cultural or hierarchical needs.
– Initiated and managed a Closing Campaign focused on wrapping up numerous longstanding projects from various departments to enhance transparency.
– Founded and managed a blog dedicated to the Control Process, devising proactive solutions targeting potential bottlenecks in the process and methods to preempt their occurrence.
– Recognised operational needs within the Project Office and took the initiative to create a comprehensive documentation manual.
Achievements:
– Successfully led the closure of nearly a hundred longstanding projects, restoring clarity and streamlining departmental workflows.
– Through the blog and other initiatives, identified and addressed key bottlenecks, significantly improving the efficiency of the control process.
– Produced a documentation manual that became a cornerstone for the Project Office, providing clear guidelines, metrics, and solutions to common issues, ultimately enhancing operational coherence and efficiency.