Associate Consultant/Consultant/Manager - Deals Analytics - CPG/TMT/Healthcare

To really stand out and make us fit for the future in a constantly changing world, each and every one of us at needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.

As a Senior Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. Professional skills and responsibilities for this management level include but are not limited to :

- Use feedback and reflection to develop self awareness, personal strengths and address development areas.

- Delegate to others to provide stretch opportunities, coaching them to deliver results.

- Demonstrate critical thinking and the ability to bring order to unstructured problems.

- Use a broad range of tools and techniques to extract insights from current industry or sector trends.

- Review your work and that of others for quality, accuracy and relevance.

- Know how and when to use tools available for a given situation and can explain the reasons for this choice.

- Seek and embrace opportunities which give exposure to different situations, environments and perspectives.

- Use straightforward communication, in a structured way, when influencing and connecting with others.

- Able to read situations and modify behavior to build quality relationships.

- Uphold the firm's code of ethics and business conduct.

Preferred Fields of Study/Experience :

- Bachelor's/Master's degree from a reputed institute in Data Science, Data Analytics, Finance, Accounting, Business Administration/Management, Economics, Statistics, Computer and Information Science, Management Information Systems, Engineering, Mathematics

- A total of 3-6 years of work experience with prior experience in analytics in the TMT (Telecom, Media, Technology)/Healthcare/Retail space to work with our Analytics Consulting practice

Preferred Knowledge/Skills :

Our team is a blend of data scientists and deal professionals teaming to bring targeted commercial insights through a blend of industry specific experience and cutting-edge data science techniques. We are looking for individuals who demonstrate knowledge and/or a proven record of success in one or both of the following areas :

Business :

- Experience working on high performing teams preferably in data analytics, consulting, and /or private equity

- Experience working in a dynamic, collaborative environment and working under time sensitive client deadlines

- Analyzing or managing accounting, financial, transactional data, and statistical methods in support of data analysis

- Understanding of financial statements, business cycles (Revenue, supply chain, etc.), business diligence, and valuation, etc.

- Strong communication and presentation skills

Technical :

- Proven track record of data extraction/transformation, analytics, and visualization approaches

- High degree of collaboration, ingenuity, and innovation to apply tools and techniques to address client questions

- Advanced skills in the following: Alteryx, Tableau and Excel

- Strong track record with leveraging business intelligence software (e.g. Tableau, PowerBI, Qlik, etc.) to turn data into insights

- Working knowledge of performing data ETL (Extract, Transform and Load), and experience with SQL, Alteryx, Power Query and other agile technologies

- Experience working with relational databases

- Exposure to Machine Learning & Advanced Analytics Techniques (but not limited to) such as Regression, Segmentation, Predictive Modelling, Pricing & Profitability analysis, Inventory Optimisation, Marketing analytics, Market mix modelling

- Knowledge and experience with basic programming: Python, R, SQL, Matlab, C++, etc.

- Knowledge of modern big data approaches preferred: e.g. PySpark, Apache Spark, Azure Databricks, Azure SQL, Azure ML, R, Python, Java, etc.