Assistant Manager

We are committed to creating a workplace for the industry’s best talent. The Smart Cube (A WNS Company) is proud to be certified as a ‘Great Place to Work’ for the fifth year running. The Smart Cube is also recognized by Great Place to Work as One of India’s Best Workplaces for Women 2021.

The Smart Cube, a global provider of strategic research and analytics solutions, has been rated on Analytics India Magazine’s (AIM) Penetration and Maturity Quadrant of Top Data Science Providers as a “Seasoned Vendor” 2022 report amongst the leading analytics service providers based out of India.

We are listed in top 50 data science organization

The Smart Cube shortlisted for two awards at the British Data Awards. Our clients include a third of the companies in the FTSE and Fortune 100, primarily in the CPG, Life Sciences, Energy, Chemicals, Industrials, Financial Services, Professional Services, and Retail sectors.

Roles and responsibilities

Specifically, Assistant Managers should –

• Understand the client objectives, and work with the Project Lead (PL) to design the analytical solution/framework. Be able to translate the client objectives / analytical plan into clear deliverables with associated priorities and constraints
• Organize/Prepare/Manage data and conduct quality checks to ensure that the analysis dataset is ready
• Explore and implement various statistical and analytical techniques (including machine learning) like linear/non-linear Regression, Decision Trees, Segmentation, time series forecasting as well as machine learning algorithms like Random Forest, SVM, ANN, etc.
• Conduct sanity checks of the analysis output based on reasoning and common sense, and be able to do a rigorous self QC, as well as of the work assigned to junior analysts to ensure an error free output
• Interpret the output in context of the client’s business and industry to identify trends and actionable insights
• Be able to take client calls relatively independently, and interact with onsite leads (if applicable) on a daily basis
• Discuss queries/certain sections of deliverable report over client calls or video conferences
• Oversee the entire project lifecycle, from initiation to closure, ensuring timely and within-budget delivery.
• Collaborate with stakeholders to gather and refine business requirements, translating them into technical specifications.
• Manage a team of data analysts and developers, providing guidance, mentorship, and performance evaluations.
• Ensure data integrity and accuracy through rigorous data validation and quality checks.
• Facilitate effective communication between technical teams and business stakeholders to align project goals and expectations.
• Drive continuous improvement initiatives to enhance data analytics processes and methodologies.
• Act as a project lead, coordinating cross-functional teams and managing project timelines and deliverables.

Client Management

• Act as client lead and maintain client relationship; make independent key decisions related to client management
• Be a part of deliverable discussions with clients over telephonic calls, and guide the project team on the next steps and way forward

Technical Requirements:

• Knowledge of how to connect Database with Knime e.g. snowflake, SQL db etc. along with SQL concepts like types of joins/union of data etc.
• Read data from a DB and write it back to a database
• Working of macros to avoid repetition of task, and enabling schedulers to run work flow(s)
• Design and develop ETL workflows and datasets in Knime to be used by the BI Reporting tool
• Perform end to end Data validation and prepare technical specifications and documentation for Knime workflows supporting BI reports.
• Develop and maintain interactive dashboards and reports using PowerBI to support data-driven decision-making.
• Lead and manage data analytics projects utilizing PowerBI, Python, and SQL to guide & deliver actionable business insights.
• Be able to succinctly visualize the findings through a PPT, a BI dashboard (Tableau, Qlikview, etc.) and highlight the key takeaways from a business perspective

Ideal Candidate

• 4-7 years of relevant advanced analytics experience in Marketing, CRM, Pricing in either Retail, or CPG industries. Other B2C domains can be considered
• Experience in managing, cleaning and analyzing large datasets using tools like Python, R or SAS
• Experience in using multiple advanced analytics techniques or machine learning algorithms
• Experience in handling client calls and working independently with clients
• Understanding of consumer businesses such as Retail, CPG or Telecom
• Knowledge of working across multiple data types and files like flat files, RDBMS files; Knime workflows, Knime server, and multiple data platforms (SQL Server, Teradata, Hadoop, Spark); on premise or on the cloud
• Basic knowledge of advanced statistical techniques like Decision trees, different types of regressions, clustering, Forecasting (ARIMA/X), ML, etc.

Other Skills

• Excellent communication skills (both written and oral)
• Ability to create client ready deliverables in Excel and PowerPoint
• Optimization techniques (linear, non-linear), and knowledge of supply chain
• VBA, Excel Macro programming, Tableau, QlikView

Education

• Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/Universities
• MBA from top tier B-schools

In interested, please share your updated CV on kiran.meghani@wns.com or apply on

https://smrtr.io/sz4-S

Looking for immediate OR early joiners