Unlock Your Potential as a Strategic Analytics Leader

6 days ago


Noida, Uttar Pradesh, India beBeeData Full time ₹ 1,80,00,000 - ₹ 2,40,00,000

Drive Business Impact as a Senior Data Analyst

As a senior data analyst, you will play a pivotal role in transforming our sales, forecasting, and retention strategies using first-principles analytics. You will distill complex go-to-market data into clear, actionable insights that improve forecast accuracy, accelerate pipeline velocity, and reduce churn.

Key Responsibilities
  • Owning the revenue intelligence foundation by building clean, reusable datasets and semantic layers across CRM, customer, and product signals defining metric logic with clear, durable definitions.
  • Quantifying risk and upside by applying statistical methods and ML where they add signal time-series for forecasting, classification/uplift for deal and renewal prioritization, survival analysis for churn.
  • Automating the feedback loop by productionizing data quality checks, anomaly detection, and alerting so insights flow into weekly operating rhythms without manual chase.
  • Turning analysis into operating decisions by forecasting with precision diagnosing variance and bias, and proposing specific changes to roll-ups, cadence, and judgment overlays that improve commit reliability.
  • Fixing funnel friction by identifying stage-to-stage drop-offs, recommending process changes (enablement, handoffs, definitions), and quantifying impact via pre/post or controlled tests.
  • Crafting compelling narratives and visuals suitable for executives ensuring clarity and ease of reuse during QBRs.
Required Skills and Qualifications
  • Strong experience in data engineering with proficiency in SQL crafting schemas for analytics slowly changing dimensions, surrogate keys, late-arriving facts building reliable pipelines/orchestration, and version-controlling code and data definitions.
  • Statistics comfort with inference and experimentation A/B, diff-in-diff, power regression/time-series uncertainty communication, and translating assumptions into business guardrails.
  • Machine learning pragmatic hands-on with supervised learning for classification/regression and survival/retention modelling ability to choose simple explainable models when they outperform complexity.
  • Business and communication mapping models to money quota coverage conversion churn packaging insights into crisp executive-ready narratives.
Benefits
  • 5–10 years in SaaS Sales/Revenue Operations analytics proven impact through measurable results.
  • Proven track record operating across modern data stacks warehouse + transformation + notebooks + BI specific tools are less important than the architectural thinking and craft you bring.
  • Education B.Tech/BE or Advanced degree in Math CS or Statistics + MBA or equivalent experience from a reputable institution.
Nice to Have
  • Experiment development in go-to-market settings policy changes enablement tests pricing/packaging experiments.
  • Exposure to MLOps concepts feature hygiene drift checks monitoring documentation culture readmes metric contracts data dictionaries.


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