REF75369V-Assistant Manager-Analytics, Python + KNIME developers, 2+ years

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.

Job Description

Roles and ResponsibilitiesAssistant Managers must understand client objectives and collaborate with the Project Lead to design effective analytical frameworks. They should translate requirements into clear deliverables with defined priorities and constraints. Responsibilities include managing data preparation, performing quality checks, and ensuring analysis readiness. They should implement analytical techniques and machine learning methods such as regression, decision trees, segmentation, forecasting, and algorithms like Random Forest, SVM, and ANN.They are expected to perform sanity checks and quality control of their 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. Assistant Managers should handle client communications independently and interact with onsite leads, discussing deliverables and addressing queries over calls or video conferences.They are responsible for managing the entire project lifecycle from initiation to delivery, ensuring timelines and budgets are met. This includes translating business requirements into technical specifications, managing data teams, ensuring data integrity, and facilitating clear communication between business and technical stakeholders. They should lead process improvements in analytics and act as project leads for cross-functional coordination.Client ManagementThey serve as client leads, maintaining strong relationships and making key decisions. They participate in deliverable discussions and guide project teams on next steps and execution strategy.Technical RequirementsAssistant Managers must know how to connect databases with Knime (e.g., Snowflake, SQL) and understand SQL concepts such as joins and unions. They should be able to read/write data to and from databases and use macros and schedulers to automate workflows. They must design and manage Knime ETL workflows to support BI tools and ensure end-to-end data validation and documentation.Proficiency in PowerBI is required for building dashboards and supporting data-driven decision-making. They must be capable of 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.Ideal CandidateCandidates should have 4–7 years of experience in advanced analytics across Marketing, CRM, or Pricing in Retail or CPG. Experience in other B2C domains is acceptable. They must be skilled in handling large datasets using Python, R, or SAS and have worked with multiple analytics or machine learning techniques. Comfort with client interactions and working independently is expected, along with a good understanding of consumer sectors such as Retail, CPG, or Telecom.They should have 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. Basic knowledge of statistical and machine learning techniques like regression, clustering, decision trees, forecasting (e.g., ARIMA), and other ML models is required.Other SkillsStrong written and verbal communication is essential. They should be capable of 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

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