Data Scientist​/Advanced Analytics Consultant

Overview

We are seeking Data Scientists and Advanced Analytics Consultants across multiple experience levels (T1‑T5) to deliver advanced analytics, statistical modeling, machine learning, and business intelligence solutions. The successful candidate will transform complex datasets into actionable insights that drive strategic and operational decision‑making. The role covers predictive analytics, customer behavior analysis, product analytics, user journey optimization, digital interface friction analysis, experimentation, and product conversion funnel optimization using modern analytics platforms, visualization tools, and machine learning technologies.

• Apply statistical analysis, predictive modeling, and machine learning techniques to solve business problems.
• Analyze structured and unstructured datasets to identify trends, patterns, and opportunities.
• Design and develop predictive, classification, clustering, and forecasting models.
• Build dashboards and interactive reports to communicate analytical insights.
• Perform user behavior analysis, customer segmentation, churn prediction, and conversion optimization.
• Analyze digital interface friction and customer journeys using product analytics platforms.
• Implement and validate client‑side and server‑side event tracking strategies.
• Design event taxonomies, data layers, and product analytics instrumentation.
• Develop A/B testing frameworks and measure experiment outcomes.
• Collaborate with business stakeholders, product teams, data engineers, and software developers.
• Validate data quality, statistical assumptions, and model performance.
• Produce clear documentation for analytical models, business insights, and reporting methodologies.
• Follow data governance, privacy, and Responsible AI best practices.

• Programming:
  Python (Pandas, Num Py, Sci Py, scikit‑learn), R.
• Data Science.
• Analytics Platforms:
  Databricks or Dataiku.
• Data Warehousing:
  Big Query or Snowflake.
• Business Intelligence & Visualization:
  Power BI, Tableau, Looker.
• Product Analytics:
  Google Analytics 4, Mixpanel, Amplitude.
• Event Tracking: client‑side, server‑side, data‑layer, tag management, product event instrumentation.
• Machine Learning:
  Regression, Classification, Clustering, Time‑Series Forecasting, Statistical Modeling.

• SQL
• Data Visualization
• A/B Testing
• Experiment Design
• Customer Analytics
• Product Analytics

• T1 – Associate Data Scientist (0‑2 Years)
  • Clean, prepare, and validate datasets for analysis.
  • Perform exploratory data analysis (EDA).
  • Build basic statistical models and visualizations.
  • Assist in dashboard development and report generation.
  • Support implementation of product analytics tracking.
  • Validate event tagging and data collection accuracy.
  • Document analytical findings and model outputs.
  • Learn business analytics methodologies and statistical techniques.
• T2 – Data Scientist (2‑4 Years)
  • Develop predictive and statistical models for business use cases.
  • Perform customer segmentation and behavioral analysis.
  • Build production‑ready dashboards and KPI reporting.
  • Implement event tracking strategies using GA4, Mixpanel, or Amplitude.
  • Analyze conversion funnels and identify optimization opportunities.
  • Perform hypothesis testing and A/B experiment analysis.
  • Collaborate with engineering teams to improve data quality.
  • Deliver analytical reports and actionable recommendations.
• T3 – Senior Data Scientist (5‑7 Years)
  • Design end‑to‑end advanced analytics and machine learning solutions.
  • Lead predictive modeling, forecasting, and optimization initiatives.
  • Design product analytics frameworks and event taxonomies.
  • Analyze digital interface friction and customer journeys.
  • Develop advanced experimentation methodologies.
  • Mentor junior data scientists and review analytical deliverables.
  • Translate business requirements into analytical solutions.
  • Improve analytical model accuracy, scalability, and business impact.
• T4 – Lead Data Scientist (8‑11 Years)
  • Lead enterprise‑wide analytics and machine learning initiatives.
  • Define analytics architecture, methodologies, and governance standards.
  • Design scalable customer analytics and product intelligence solutions.
  • Drive advanced…