Assistant Manager-Analytics

The Smart Cube, a WNS company, is a trusted partner for high performing intelligence that answers critical business questions. We work with our clients to figure out how to implement the answers, faster. As an Assistant Manager, you will be responsible for understanding client objectives and collaborating with the Project Lead to design effective analytical frameworks. You should translate requirements into clear deliverables with defined priorities and constraints. Your responsibilities will include managing data preparation, performing quality checks, and ensuring analysis readiness. You will implement analytical techniques and machine learning methods such as regression, decision trees, segmentation, forecasting, and algorithms like Random Forest, SVM, and ANN. It is important to perform sanity checks and quality control of your own work as well as that of junior analysts to ensure accuracy. The ability to interpret results in a business context and identify actionable insights is critical. You will handle client communications independently and interact with onsite leads, discussing deliverables and addressing queries over calls or video conferences. Managing the entire project lifecycle from initiation to delivery, ensuring timelines and budgets are met, translating business requirements into technical specifications, managing data teams, ensuring data integrity, and facilitating clear communication between business and technical stakeholders will also be part of your role. Leading process improvements in analytics and acting as project leads for cross-functional coordination are expected. In terms of technical requirements, you must be proficient in connecting databases with Knime (e.g., Snowflake, SQL) and understand SQL concepts such as joins and unions. You should be capable of reading/writing data to and from databases, using macros and schedulers to automate workflows, designing and managing Knime ETL workflows to support BI tools, and ensuring end-to-end data validation and documentation. Proficiency in PowerBI is required for building dashboards and supporting data-driven decision-making. Leading analytics projects using PowerBI, Python, and SQL to generate insights, visualizing key findings using PowerPoint or BI tools like Tableau or Qlikview is essential. The ideal candidate should have at least 4-7 years of experience in advanced analytics across Marketing, CRM, or Pricing in Retail or CPG. Experience in other B2C domains is acceptable. Skills in handling large datasets using Python, R, or SAS, working with multiple analytics or machine learning techniques, client interactions, and working independently are expected. A good understanding of consumer sectors such as Retail, CPG, or Telecom is essential. Experience with various data formats and platforms including flat files, RDBMS, Knime workflows and server, SQL Server, Teradata, Hadoop, and Spark on-prem or in the cloud is required. Basic knowledge of statistical and machine learning techniques like regression, clustering, decision trees, forecasting (e.g., ARIMA), and other ML models is necessary. Strong written and verbal communication skills are essential for creating client-ready deliverables using Excel and PowerPoint. Knowledge of optimization methods, supply chain concepts, VBA, Excel Macros, Tableau, and Qlikview will be an added advantage. Qualifications required include Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/Universities, and MBA from top tier B-schools.,