Sr Data Analyst II (Content Flow Analytics) Would you like to be part of a team that delivers high-quality software to our customers? Elsevier Health applies innovation, facilitates insights, and helps drive more informed decision-making for our customers across global health. We support health providers by providing accessible, trusted evidence-based information; prepare more medical and nursing students with effective tools and resources; provide insights that help clinicians improve patient outcomes; and supports a more personalized and localized healthcare experience. The Senior Data Analyst II leads the end-to-end delivery of analytics and reporting that improve content-flow performance , strengthen data-driven decision making , and accelerate continuous improvement across global Operations. This role operates with a high degree of independence—translating ambiguous business questions into structured hypotheses, building the right data products (dashboards, KPI frameworks, deep-dive analysis), and influencing senior stakeholders through clear, story-led insights.
the role is expected to bring/build a strong understanding of the content journey and operational handoffs, including linked data (CP/LD). (Content production/management interfaces, supplier touchpoints, workflow steps, quality gates, exceptions/rework loops, throughput and cycle time drivers). The role partners closely with Operations leadership and adjacent teams (e.g., Strategy, Content production operations teams, Finance, Analytics CoE, IT/ Data Warehousing teams) to ensure consistent metrics, trusted data foundations, and measurable operational outcomes.
A Senior Data Analyst II is a recognised analytics expert within their domain, increasingly shaping not just outputs but also how the organisation thinks about metrics, quality, and performance management . Proactively identify problem areas in the content journey (bottlenecks, defect leakage, rework, delay drivers, supplier variability, workload imbalance) and propose targeted analyses and corrective actions.
Present insights and recommendations in compelling, non-technical narratives—tailored to stakeholder context, decision points, and operational realities.
Support senior leaders through decision cycles by offering options, trade-offs, impact sizing, and monitoring plans.
Ensure delivery of reports/dashboards/BI structures that meet business requirements and support ongoing trend and performance analysis.
adoption plan to embed usage into BAU operations
Deliver accurate and timely KPI reporting across all relevant stakeholder levels, enabling clear identification of performance focus areas.
Partner with Data Management to publish trusted dashboards to Operations users and senior governance forums with consistent definitions and strong data quality controls.
3) Publishing Domain and Content-Flow Process Analytics
Apply deep understanding of publishing/content operations to interpret workflow behaviour and identify improvement opportunities.
Build and maintain measurement frameworks for content flow, such as:
throughput and cycle time analysis (lead time, queue time, touch time)
stage-level performance and handoff quality
exception/rework drivers, defect trend analysis, root cause themes
supplier performance variation and operational risk hotspots
4) Data Preparation, Integration, and Engineering Literacy
combine data from multiple systems and sources using SQL and modern analytics tooling.
Demonstrate strong understanding of data integration mechanics and data engineering concepts (pipelines, transformations, joins, grain, lineage, refresh cadence, performance constraints).
Work effectively with big data platforms and tools (Databricks preferred) and demonstrate fluency in:
SQL (essential)
Python (desirable) and/or Scala (desirable, not essential)




additional tooling such as / similar to KNIME, Tableau/Power BI, and warehouse technologies (Snowflake exposure is an advantage)
Act as a bridge between business needs and technical implementation—ensuring solutions are scalable, maintainable, and aligned to platform standards.
Undertake complex analyses using statistical and analytical techniques appropriate to the problem, including:
trend decomposition, segmentation, and cohort analysis
outlier/anomaly detection and exception monitoring
hypothesis testing, correlation/association exploration, scenario modelling
Develop (or continue developing) advanced analytics capabilities such as predictive analytics, basic machine learning applications, and NLP use cases where relevant to content operations.
Translate modelling outputs into operational recommendations, guardrails, and monitoring metrics (not just model accuracy).
6) Data Governance, Quality, and Metric Consistency
Ensure governance for quality, integrity, completeness, timeliness, and reliability so reporting is trustworthy.
Carry out regular data quality assessments in recent and existing reporting solutions; Lead (or co-lead) documentation practices: data definitions, KPI logic, reporting change logs, refresh schedules, and known limitations.
Act as an influencer for data quality culture—motivating stakeholders to treat data trust as foundational to performance management.
7) Coaching, Enablement, and Analytics Community Leadership
Coach and support junior analysts: data preparation, modelling approaches, visualization standards, stakeholder management, and project execution.
Provide training and ongoing support to reporting champions and business users to ensure consistent and effective reporting usage.
8) Project and Program Contribution
Lead medium/tactical analytics projects, managing tasks, blockers, timelines, and stakeholder expectations with minimal oversight.
Participate in international programs and projects requiring analytics/BI expertise; Provide detailed analysis and documentation to support project planning and resourcing; Represent the analytics function in governance discussions and ensure decisions are communicated clearly to the wider reporting community.
Requirements (Qualifications & Experience)
Bachelor’s degree required; preference for quantitative disciplines (Economics, Math, Statistics, Data Science, Engineering, or similar).
Master’s/PhD is a plus (particularly for modelling-heavy work).
Experience
Typically, 5–8 years in data analytics / business analytics, ideally within a global multinational environment.
Preference for demonstrated exposure to publishing operations and content-flow processes or equivalent process-heavy operations domains.
Strong SQL skills and comfort working with large datasets.
High proficiency in visualization/reporting tools (Tableau and/or Power BI).
Excellent communication and presentation skills—able to tell clear, decision-oriented stories with data for non-technical audiences.
Databricks experience (preferred).
Python and/or Scala exposure (desirable, not essential).
Snowflake experience (advantage).
Experience with KNIME or similar tooling.
Familiarity with data warehousing and modern analytics architectures.
identifies most relevant analyses/metrics; helps set goals aligned to business objectives.
Data Preparation: Expert at blending/preparing data across tools and big data platforms; Data Modelling:



Applies advanced analysis scenarios and statistical approaches; Data Visualization: Support Data-Driven Culture: Advanced understanding of content-flow/publishing operations; Project Management: Leads medium/tactical analytics projects; Champion talent through timely feedback, coaching, and practical development plans.
Drive Commercial Edge
Prioritize customers by using data to identify experience gaps and predict future requirements.
Value data by using benchmarks, monitoring accuracy, and turning evidence into practical improvements.
Deliver sustainable performance through reliable execution, ownership, and learning-oriented accountability.
Manage complexity by navigating ambiguity, making considered decisions, and taking calculated risks.
Build connections by strengthening networks and working effectively across cultures and geographies.
Stakeholders use the delivered dashboards and insights consistently to run performance conversations and drive actions.
Content-flow bottlenecks and quality pain points are quantified, explained, and improved through measurable interventions.
data trust improves through strong governance and documentation.
Junior analysts and reporting champions become more capable due to structured coaching and enablement.
Analytics delivery becomes faster, more scalable, and more embedded into BAU operations.
We promote a healthy work/life balance and provide various well-being initiatives, shared parental leave, study assistance, and sabbaticals to help you meet both your immediate responsibilities and long-term goals.
Comprehensive Health Insurance: Covers you, your immediate family, and parents.
Enhanced Health Insurance Options: Competitive rates negotiated by the company.
Group Life Insurance: Ensuring financial security for your loved ones.
Extra protection for accidental death and permanent disablement.
Flexible Working Arrangement: Achieve a harmonious work-life balance.
Employee Assistance Program: Medical Screening: Your well-being is a top priority.
Long-Service Awards: Recognizing dedication and commitment.
New Baby Gift: Celebrating the joy of parenthood.
Subsidized Meals in Chennai: Enjoy delicious meals at discounted rates.
Various Paid Time Off: Take time off with Casual Leave, Sick Leave, Privilege Leave, Compassionate Leave, Special Sick Leave, and Gazetted Public Holidays.
Free Transport pick up and drop from the home -office - home. (We are a global leader in information and analytics, helping researchers and healthcare professionals' advance science and improve health outcomes. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science, research, health education, interactive learning, and exceptional healthcare and clinical practice. We harness innovative technologies to support science and healthcare, partnering for a better world. We combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. What you do every day will help advance science and healthcare to advance human progress
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