Data Scientist / Advanced Analytics Consultant
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Key skills for this role
About the Role
We are seeking Data Scientists and Advanced Analytics Consultants across multiple experience levels (T1 T5) to deliver advanced analytics, statistical modeling, machine learning.
Key Skills for This Role
Responsibilities
- 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
Requirements
- Proficiency in Python (Pandas, NumPy, SciPy, scikit learn)
- Experience with data science platforms like Databricks or Dataiku
- Experience with data warehousing solutions like BigQuery or Snowflake
- Proficiency in BI tools like Power BI, Tableau, or Looker
- Experience with product analytics tools like GA4, Mixpanel, or Amplitude
- Knowledge of event tracking and data collection strategies
- Strong understanding of machine learning techniques (regression, classification, clustering, time series)
- Experience with A/B testing and experiment design
- Strong SQL skills
Full Job Posting
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.
Key Responsibilities
- 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.
Required Technical Skills
- Programming & Statistical Analysis: Python (Pandas, NumPy, SciPy, scikit learn), R
- Data Science & Analytics Platforms: Databricks or Dataiku
- Data Warehousing: BigQuery or Snowflake
- Business Intelligence & Visualization: Power BI or Tableau or Looker
- Product Analytics: Google Analytics 4 (GA4) or Mixpanel or Amplitude
- Event Tracking & Data Collection: Client side Event Tracking, Server side Event Tracking, Data Layer, Tag Management, Product Event Instrumentation
- Machine Learning: Regression, Classification, Clustering, Time Series Forecasting, Statistical Modeling
- Additional Skills: SQL, Data Visualization, A/B Testing, Experiment Design, Customer Analytics, Product Analytics
Responsibilities by Tier
- T1 Associate Data Scientist (0 2 Years): Clean, prepare, and validate datasets; perform EDA; build basic models and visualizations; assist in dashboard development; support product analytics tracking.
- T2 Data Scientist (2 4 Years): Develop predictive and statistical models; perform customer segmentation; build production ready dashboards; implement event tracking; analyze conversion funnels; perform A/B analysis.
- T3 Senior Data Scientist (5 7 Years): Design end to end analytics and ML solutions; lead predictive modeling; design product analytics frameworks; develop advanced experimentation; mentor juniors.
- T4 Lead Data Scientist / Advanced Analytics Lead (8 11 Years): Lead enterprise wide analytics initiatives; define analytics architecture; drive advanced experimentation; lead stakeholder engagements; mentor teams.
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