Deal Advisory, Value Creation

**Function(s)**:Advisory

**Work Type**:Permanent

**Start Date for Applications**:13 Jan 2025

**Closing Date for Applications**:
KPMG in Singapore is part of a global organization of independent professional services firms providing Audit, Tax and Advisory services. We operate in 143 countries and territories with more than 273,000 partners and employees working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients.
Job DescriptionKPMG in Singapore is part of the KPMG’s global network of professional services firms. KPMG firms operate in 143 countries and territories with more than 265,000 partners and employees working in member firms around the world, serving the needs of our clients.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.
- 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.
- 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.
- 3 - 7 years of experience in data science or data analytics roles, AI, operational research
- 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
- Machine learning / deep learning libraries (e.g., pandas, scikit-learn, Keras, TensorFlow, PySpark)
- Predictive modelling, advanced statistical modelling and hypothesis testing (e.g. regression analysis, time series analysis, clustering, classification, predictions)
- Familiarity with natural language processing (NLP)
- Data cleaning and preprocessing techniques, features engineering / selection to enhance model performance, features importance to explain the model
- Optimization techniques and tools (e.g. linear programming, mixed-integer programming)
- Azure cloud platform, Azure Machine Learning, Azure Data and AI tools, Azure Databricks for big data processing and machine learning pipeline management
- 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)
- Expertise in generative AI models (e.g. GPT). Experience in building, fine-tuning, and deploying large language models (LLMs) and transformer architecture
- Advantages with following knowledge and skillsets:

- GitHub /