Analyst – BI & Data

We are seeking a highly detail‑oriented Data Analyst to support the Strategic Growth Team (SGT), US, with executive‑level reporting, analytics, and opportunity review. This role is central to strengthening data quality, ensuring timely insights for senior leadership, and maintaining reporting accuracy that meets the expectations for executive consumption.

In addition to core reporting responsibilities, the analyst will assist with opportunity review during non‑peak reporting periods.

The ideal candidate brings strong analytical capability, impeccable attention to detail, and an excellent understanding of CRM/Sales systems, with proven experience in reporting for senior audiences.

This role will be based in the Noida/ Bengaluru office.

Qualifications

Key Competencies / Skills / Qualifications

Masters in Computer Science/Statistics/Maths/Information Technology

• Relevant domain certifications

• Proven work experience of 4-7 years as a Data Analyst or similar role

• Technical expertise regarding data models, database design development, data mining, and segmentation techniques

• Strong experience with SQL, Python/R, Excel, and enterprise BI tools (Tableau, Power BI).

• Solid understanding of Sales CRM systems, preferably Horizon or other enterprise CRM environments.

• Ability to analyze large datasets, identify anomalies, and provide actionable insights.

• Strong communication skills to present findings clearly to both technical and non‑technical stakeholders.

• Proven ability to manage competing tasks without compromising data accuracy or deadlines.

BGV:

• Employment with WSP India is subject to the successful completion of a background verification (“BGV”) check conducted by a third-party agency appointed by WSP India.

• Candidates are advised to ensure that all information provided during the recruitment process — including documents uploaded — is accurate and complete, both to WSP India and its BGV partner”.

Responsibilities

Executive Reporting & Analytics

• Develop, maintain, and deliver executive-level dashboards and reports with zero‑defect accuracy, supporting US leadership’s strategic decision‑making.

• Analyze large, complex datasets to identify trends, exceptions, and opportunities for process improvement.

• Validate weekly and monthly reporting inputs to ensure completeness and correctness, addressing the gaps previously observed in team reporting.

• Collaborate with SGT leaders to clarify reporting requirements and ensure output meets expectations.

Data Quality, Governance & System Support

• Conduct data audits, cleanse datasets, and troubleshoot discrepancies across system.

• Partner with technical teams to recommend improvements to data flows and business processes.

• Support review of missing or incorrect data fields in opportunities and take corrective actions aligned with Horizon standards.

• Assist with structural data requirements for new software tools and maintain accurate data models.

Opportunity Review

• Provide supplemental support for opportunity review during workload surges, ensuring SGT remains current on weekly pipelines as directed by leadership.

• Prioritize core reporting tasks before accepting additional intake—reflecting leadership’s requirement that reporting accuracy must not be compromised by backlog work.

Collaboration & Stakeholder Communication

• Work closely with Horizon Sales Administrators and PMs.

• Proactively communicate blockers or data issues and recommend solutions for continuous improvement.

• Work with management to prioritize business and information needs and propose solutions and strategies to business challenges

• Analyze and interpret trends or patterns in complex data sets using statistical techniques and provide ongoing reports

• Acquire data from primary or secondary data sources and undertake pre-processing of structured and unstructured data

• “Clean” data by reviewing performance indicators to locate and correct code problems

• Create and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality

• Analyse structural requirements and advise data architecture for new software and applications development by collaborating with engineering and product development teams

• Locate and define new process improvement opportunities and identify valuable data sources to automate collection processes

• Where essential, propose migration of data from legacy systems to new solutions

• Design conceptual and logical data models and flowcharts. Present information using data visualization techniques

• Build predictive models and machine-learning algorithms