Deal Advisory, Data Scientist, Assistant Manager to Manager

We are growing our Deal Strategy and Value Creation team in Singapore. We are looking for high calibre candidates to join our team and be part of the exciting growth plans we have for this area of the business. Our Deal Advisory practice provides holistic, data-driven client solutions in relation to acquisitions, disposals, joint ventures, buy-outs, market entry, financing, and other M&A transactions. We advise clients on their deal strategy and assist to create value by identifying and delivering upsides and opportunities from their Deals. Our clients include private equity firms, financial institutes and corporates from various industries. Our team comes from a variety of backgrounds and nationalities and have a diverse and dynamic environment that embraces and values differences. We invest substantially in professional development of our team members, with particular emphasis on coaching. We offer a collaborative and flexible working environment, with due consideration of work-life balance and changing demands of personal or family life. This role will leverage your technical expertise in data science and machine learning to solve real-world business problems, while gaining exposure to business strategy, value creation, and management consultancy. You will have opportunities to work closely with senior advisors and business leaders, deepen your understanding of business optimization, mergers & acquisitions, financial restructuring, and other high-impact areas within the Deal Advisory space for various industries. Through hands-on projects, you'll learn how data-driven insights directly contribute to strategic decision-making and business growth. Responsibilities: Collaborate with cross-functional teams to gather and analyse data for mergers, acquisitions, valuations, restructuring, business performance improvements and other strategic advisory projects. Apply Data Science / Gen AI skills to real-world business problems, aiming to identify actionable insights that may create values and positive impacts for our clients. Load and preprocess large, complex datasets (structured and unstructured) to make them usable for predictive modelling, statistical analysis and visualization. Develop predictive models, machine learning algorithms, Gen AI models and statistical models to identify trends, risks and opportunities in the data. Apply optimization techniques to solve business problems related to resource allocation, pricing and other business and operational aspects. Generate actionable business insights based on the processed data, transforming analytical results and models into clear data-driven recommendations for stakeholders. Create compelling data visualization and dashboard using tools like Power BI, Tableau to communicate findings and tell stories effectively. Present findings to senior management and clients, helping them leverage data science models to optimize their strategic and operational decisions Requirements: Bachelor's degree or above in Data Science, Computer Science, Statistics, Applied Mathematics, or related field. Master's degree in data science and AI will be beneficial. Minimum 5 to 8 years of experience in data science or data analytics roles, AI, operational research. Ability to generate actionable insights from data, going beyond numbers to make meaningful business recommendations. Effective communication skills, with the ability to explain complex models and results to non-technical stakeholders. Experience in financial analysis, understanding of corporate finance and deal structuring is a plus. Problem-solving mindset with a focus on delivering results in high-pressure, time-sensitive environments. Ability to collaborate with diverse teams and work on multiple projects simultaneously. Strong proficiency in Python, Alteryx, Power BI (or Tableau) are essential. Hands-on experiences on the following:Alteryx (incl. macro and analytic app) to build workflow for data analysis and insights generations Operational research including mathematical optimization models and solver tools (e.g. linear programming, mixed-integer programming) Machine learning / deep learning python libraries (e.g., pandas, scikit-learn, Keras, TensorFlow, PySpark, etc.) Predictive modelling, advanced statistical modelling and hypothesis testing (e.g. regression analysis, time series analysis, clustering, classification, predictions, A/B testing) Expertise in generative AI models (e.g. GPT). Experience in building, fine-tuning, and deploying large language models (LLMs) and transformer architecture. Familiarity with natural language processing (NLP) Azure cloud platform, Azure Machine Learning, Azure Data and AI tools, Azure Databricks for big data processing and machine learning pipeline management Data cleaning and preprocessing techniques, features engineering / selection to enhance model performance, features importance to explain the model Data visualization using tools to develop data story, e.g., Matplotlib, Seaborn, Power BI / Tableau. SQL skills and knowledge of relational databases (e.g. MySQL) Advantages with following knowledge and skillsets:GitHub / Containers technology / DevOps / software development and deployment. Big data engineering tasks and tools (e.g. ETL pipelines, data warehouses, Apache Spark, Kafka, etc.). Other language skills, e.g. R, Scala Certifications in AI and / or machine learning from Microsoft Azure Only shortlisted candidates will be contacted by KPMG Talent Acquisition team, personal data collected will be used for recruitment purposes only.