Senior Data Scientist – Day Rate Contract GTM Experimentation experience with causal libraries such as DoWhy, EconML, or similar is preferred).
·Advanced SQL skills with experience working on large-scale data warehouses.
·Experience designing and analyzing online or field experiments.
·Ability to communicate, justify and visualize complex statistical concepts for non-technical stakeholders.
Preferred ·Experience in B2B GTM environments (SFDC and MarTech data, sales performance, pricing, marketing mix, lifecycle optimization, or growth experimentation).
·Familiarity with uplift modeling and heterogeneous treatment-effect estimation.
·Exposure to Bayesian methods or hierarchical modeling.
·Experience deploying models in production environments.
·Experience influencing executive decision-making through formal experimentation readouts or investment cases.
What Success Looks Like ·Experiment design standards improve across Sales, Customer Success, and other GTM teams.
·Reusable measurement frameworks reduce ad hoc analyses and increase organizational rigor.
·Incrementality and experimentation become core decision-making inputs across GTM.
·Resource allocation decisions are guided by defensible causal estimates rather than correlational metrics.
·Clear linkage between experimental evidence and capital allocation decisions.
Impact This role directly shapes how the organization measures success.
You will influence how capital is deployed across channels, how programs are evaluated, and how growth strategies are validated.
The mandate is not incremental reporting improvement, but a structural shift toward causal decision-making.
For more information please call Michael on 01- or e: