Deep Learning Engineer and highly experienced Data Scientist with over 15 years in consulting and technical environments, including 12+ years focused on machine learning, deep learning, and machine learning operations. Expertise spans various sectors such as insurance, finance, retail, marketing, e-commerce, IT, and healthcare. Excels in developing and implementing end-to-end ML/data pipelines, covering data ingestion, cleaning, transformation, model training, evaluation, and production deployment. With hands-on experience in designing data products and applying machine learning techniques to complex datasets, ensures meticulous evaluation of multiple solutions. Effectively balances technical expertise with strategic vision, formulating comprehensive roadmaps for the ideation and deployment of data products across enterprises. Proficiency in data modeling allows for the extraction of actionable insights and the presentation of complex concepts intuitively to senior management. As an experienced leader, has successfully managed teams of over 70 members across global locations, demonstrating a proven ability to balance people management with technical skills. Possesses outstanding analytical, problem-solving, and communication skills, with full work rights in Australia and a postgraduate degree in applied statistics. Committed to writing production-quality code that adheres to software engineering best practices and MLOps principles, ensuring the development of robust and scalable machine learning applications.
– Designed and developed (end-to-end) a prototype in predictive AI model by using machine learning (ML)/deep learning algorithms, data science, computer vision and NLP.
– Co-ordinated with the Co-Director in developing and execution of healthcare applied research projects using statistical analysis and machine learning algorithms.
– Gathered, documented, and analysed data analytics requirements with a view to model and predict the risk-factor for older people to move from home care to aged care.
– Conceived ideation, developed prototype, conducted extensive evaluation, and deployed in production. Assist with a range of data preparation activities including checking and editing
datasets for consistency, creating derived and harmonised variables, and reporting on their properties according to study/project procedures.
– Developed solutions in building complex data-science problems to solve healthcare problem and mentored younger members of the team to achieve results.
We aim to leverage the abundance of public textual data in social media to provide automatic “discovery” of new, potential Farmer-to-Consumer (F2C) markets. The same technology will allow discovery of other emerging trends such as new food habits, preferences, styles, and, more so, over a variety of languages. Our eventual aim is to provide the partners of organisation and the Australian agri-food industry with a new, AI-based competitive edge and ability to deal with the international market by using machine translation through Natural Language Processing (NLP). As part of this role, I have been conducting the below activities:
– Developed novel predictive analytics algorithms for agri-food and health sector, application of which increased yearly crop production by 6%. Used machine learning techniques called
Random Forest and Xgboost to predict Australian crop price. Also developed a deep learning model to conduct plant disease classification and detection using yolo and open CV.
– Developed machine learning models to automatically discover trends in food and health. Demonstrated multi-million dollars savings by leveraging ML model to identify defaulters in crop
insurance with accuracy rate of 78% and taking actions based on that.
– Performed requirements analysis, created problem statement, and developed strategies on which data is required, which specific data analysis, manipulating data using SQL, statistical
modelling methodology to be used, finding patterns, clustering, correlation, trends, and reporting via visualisations.
– Exuded commercial acumen, impressive interpersonal skills and relationship building skills. Collaborated and communicated effectively with internal and external stakeholders to
brainstorm, breakdown requirements in actionable tasks.
– Designed experiments, solutions, applied machine learning algorithms and techniques to develop sophisticated predictive modelling to solve complex agri-food, healthcare and financial
business problems
– Evaluated different analytical approaches, designed, and implemented new predictive statistical modelling algorithm that deliver better modelling outcomes than various existing
modelling methodologies.
– Implemented end-to-end ML pipelines, writing complex queries using SQL, right from ETL/ELT to model training, evaluation, model testing and monitoring and deployment to production.
– Led solutions to complex data-science problems and mentored younger members of the team to achieve results. Transformed complex business problems into clear business recommendations.
– Created visual reports on intended variables’ performance, mining a massive set of data by using tools such as Python, Matplot, Seaborn, Gephi. Prepared data visualisation, identified
trends, and interpreted actionable insights. Conducted storytelling.
– Analysed various client companies’ current profile and collected data about areas requiring urgent improvements. Delivered data driven solutions to clients’ problems by providing
consulting services, analysing requirements, setting up experiments, building ML models, deploying to the proposed solutions.
– Led end-to-end design and development of scalable data-intensive/AI solutions along with building efficient ETL dataflows using Airflow, MLOps pipelines for smooth deployment and
maintenanceof ML application.
– Built and monitored CI/CD/Retraining pipelines for different deployment strategies.
– Developed an AI assistance product for C-level professionals by leveraging deep learning techniques to convert speech to text then summarize the text using autoencoders and translate
to other languages (when necessary) with an accuracy of 77%.
– Proficient in extracting, analyzing and manipulating data using SQL and python.
– Implemented ML models to predict financial loan repayment defaulters saving up to $ 21 million for a client by using the variables such as applicant’s income, co-borrower income,
defaulter or not, assets, liabilities, EMI, etc. Achieved accuracy rate of 81%.
– Increased the customer base of a retail supermarket by 7% in 3 months by first understanding the market and customer base, then segmenting the customer and further using marketing mix
model (MMM) and customer life-time values (CLT) techniques and employing those in a ML model.
– Successfully built and led a large team of data scientists by mentoring them.
– Effectively navigated change and disruption. Led teams to make informed business decisions towards achieving strategic goals and delivering value-based insights.
– Applied machine learning/NLP, statistics and optimization techniques on unstructured datasets for different verticals including insurance and automobile parts manufacturing clients.
– Worked as part of a cross-functional team on diverse data centric projects on advanced analytics platforms to build scalable and reusable machine learning solutions leveraging MLOps.
Designed and implemented an end-to-end big data pipeline using SQL, Airflow, Python, ETL techniques.
– Built and maintained relationships with key stakeholders, built and led different teams of data scientists to develop solutions for clients’ complex data centric problems.
– Built predictive models for an insurance client to accurately predict risk score of a prospective client, resulting in better decision making during new client intake saving $13M in
undue insurance claims.
– Developed predictive model by using machine learning tree based and ensemble methods to detect faults in automobile parts based on telematics and diagnostics data before parts
breakdown. Reduced automobile expenses by $15M
– Developed predictive model to match hand-written signature for a banking client by using convolution neural networks. Achieved an accuracy of 84.4 % to detect financial loan
defaulters and fraudulent activities by using this method.
– Designed and developed face recognition techniques for a retail chain by using open CV and yolo techniques.
– Developed advanced classification techniques by using deep learning techniques with an accuracy of 79%.
– Enhanced revenue by 12.5 % in a 5-month period.
– Developed an AI assistance model by leveraging ML, SQL, timeseries to assist them with taking AI insight into account for predicting future business state for a strategic decision
taken at present time.
– Developed and implemented data centric solutions to best fit business problems by applying digital transformation processes from a standard statistical tool or custom algorithm
development.
– Developed Advanced Analytics models to better understand the customers’ choice by first segmenting and targeting them to provide offers, and then sending them discounts to promote
sales using marketing mix model and multi-touch attribution models.
– Built advanced analytic solutions and high impact data models by using cutting edge data mining, machine learning (ML), SQL and statistical modelling to generate business insights for
significant business values.
– Created data models from multiple disparate sources with the goal of discovering insights that contributed to
achieving 11% increase in customer retention.
– Enhanced techniques for customer segmentation to target a specific group of people by using ML models.
– Achieved accuracy rate of 76.4% resulting in reduction to customer churn by 9%.
– Designed and executed advanced analytics solutions (machine learning/ predictive/ETL methods) for complex financial business problems by using industry best practice tools,
technologies, and methods to generate insights on financial markets.
– Delivered predictive financial models to an impressive range of clients influencing their businesses as never before and making a positive impact on their success by leveraging
advanced analytics and tools.
– Applied statistical analysis, data mining techniques, and built high quality prediction systems. Performed advanced analytics and data modelling to generate proper business insights
to deliver values to clients.