Company Description
The Smart Cube, a WNS company, is a trusted partner for high performing intelligence that answers critical business questions. And we work with our clients to figure out how to implement the answers, faster.Roles and ResponsibilitiesAssistant Managers are expected to understand client objectives and collaborate with the Project Lead to design appropriate analytical solutions. They should be able to translate business goals into structured deliverables with defined priorities and constraints. The role involves managing, organizing, and preparing data, conducting quality checks, and ensuring readiness for analysis.They should be proficient in applying statistical and machine learning techniques such as regression (linear/non-linear), decision trees, segmentation, time series forecasting, and algorithms like Random Forest, SVM, and ANN. Sanity checks and rigorous self-QC of all outputs, including work from junior analysts, are essential to ensure accuracy.Interpretation of results in the context of the client’s industry is necessary to generate meaningful insights. Assistant Managers should be comfortable handling client calls independently and coordinating regularly with onsite leads when applicable. They should be able to discuss specific deliverables or queries over calls or video conferences.They must manage projects from initiation through closure, ensuring timely and within-budget delivery. This includes collaborating with stakeholders to refine business needs and convert them into technical specifications, managing data teams, conducting performance evaluations, and ensuring high data quality. Effective communication between technical and business stakeholders is key to aligning expectations. Continuous improvement of analytics processes and methodologies is encouraged. The role also involves leading cross-functional teams and overseeing project timelines and deliverables.Client ManagementAssistant Managers will act as the primary point of contact for clients, maintaining strong relationships and making key decisions independently. They will participate in discussions on deliverables and guide project teams on next steps and solution approaches.Technical RequirementsCandidates must have hands-on experience connecting databases with Knime (e.g., Snowflake, SQL DB) and working with SQL concepts such as joins and unions. They should be able to read from and write to databases, utilize macros to automate tasks, and enable schedulers to run workflows. The ability to design and build ETL workflows and datasets in Knime for BI reporting tools is crucial. They must perform end-to-end data validation and maintain documentation supporting BI reports.They should be experienced in developing interactive dashboards and reports using PowerBI and leading analytics projects using PowerBI, Python, and SQL. Presenting insights clearly through PowerPoint or BI dashboards (e.g., Tableau, Qlikview) is also expected.Ideal CandidateThe ideal candidate will have 4 to 7 years of relevant experience in advanced analytics for Marketing, CRM, or Pricing within Retail or CPG; other B2C sectors may also be considered. Experience in managing and analyzing large datasets using Python, R, or SAS is required, along with the use of multiple analytics and machine learning techniques.They should be able to manage client communications independently and understand consumer-facing industries such as Retail, CPG, or Telecom. Familiarity with handling various data formats (flat files, RDBMS) and platforms (Knime, SQL Server, Teradata, Hadoop, Spark) in both on-premise and cloud environments is expected. A solid foundation in advanced statistical techniques such as regressions, decision trees, clustering, forecasting (ARIMA/X), and machine learning is essential.Other SkillsStrong verbal and written communication is a must. The candidate should be able to deliver client-ready outputs using Excel and PowerPoint. Knowledge of optimization techniques (linear/non-linear), supply chain concepts, VBA, Excel Macros, Tableau, and Qlikview is a plus.Qualifications
Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/UniversitiesMBA from top tier B-schools
