Satori Analytics

Technical Recruiter

• Own end-to-end recruitment for technical roles across multiple seniority levels.
• Partner with hiring managers to define role requirements and hiring strategies.
• Source and engage top tech talent through proactive outbound approaches.
• Manage interview processes and ensure an excellent candidate experience.
• Track recruiting metrics and optimize pipelines for speed and quality.

Tech Talent Acquisition Specialist

Data Analyst

• Design, develop, and execute below-the-line targeted campaigns — covering migration, renewal, upsell, and cross-sell — aligned with enterprise mobile commercial objectives
• Own the full campaign lifecycle — audience selection, offer definition, channel strategy, scheduling, and post-campaign evaluation
• Track and optimise campaign performance against key metrics (conversion rate, revenue uplift, NPS) and drive optimisation opportunities
• Analyse customer datasets to identify behavioural patterns, commercial opportunities, and target populations
• Build and refine customer segmentation models using analytical and data-mining tools (primarily IBM SPSS Modeller)
• Translate commercial briefs into precise data definitions and campaign audiences
• Prepare and maintain campaign performance reports and presentations for business stakeholders
• Partner with cross-functional teams (Product, Analytics, Sales, Finance, CRM), providing data and insight inputs
• Translate analytical findings into clear, decision-ready summaries

CRM Data Analyst

Data Scientist

• **What Your Day Might Look Like:**
• - Specify Bayesian regression models from scratch — likelihood, priors, hierarchical structure — not just library defaults
• - Build and diagnose models in PyMC and/or Stan — MCMC sampling, convergence diagnostics (R-hat, ESS, divergences), and posterior visualisation with ArviZ
• - Design hierarchical structures with partial pooling and multi-level architectures, handling sparse group data gracefully
• - Chain models correctly — sequential, multi-stage architectures with full uncertainty propagation (Monte Carlo through the chain, never point estimates)
• - Model media dynamics — adstock and saturation transformations (geometric, Weibull, Hill), with parameters specified via priors and response curves extracted from posteriors
• - Optimise budgets under constraints — scipy.optimize and CVXPY for channel floors/ceilings and portfolio constraints, plus multi-objective work (Pareto frontiers, weighted utility, conflicting objectives)
• - Establish causal ground truth — geo experiment design and analysis, Difference-in-Differences, Synthetic Control, and experiment-to-model calibration
• - Handle structural breaks — piecewise regression, change-point detection (PELT, BOCPD, Bayesian), and regression discontinuity design
• - Document your work — methodology docs, assumption logs, and structured write-ups that stand up to scrutiny

Data Scientist – MMO Enhancements

• Design and build customer segmentation solutions on payment transaction data, from feature engineering through clustering to business-ready segment narratives
• Engineer behavioural features at scale — multi-window RFM, spend trajectory, recency decay, and time spine construction on transactional datasets
• Validate and stress-test clusters using silhouette scores, stability testing, and — most importantly — business interpretability
• Explain your models using SHAP, translating feature importance into plain-English segment stories for non-technical stakeholders
• Calculate and interpret competitive metrics such as Spend Index (issuer view) and Wallet Share (merchant view), including a correct treatment of network coverage limitations
• Build media planning logic — temporal disaggregation of coarse budgets into monthly plans (Denton-Cholette or equivalent), heuristic channel splits, and MMO response curve integration
• Handle data filtering with rigour — BIN/ICA logic for issuer data, merchant_parent_name logic for merchant data
• Document your work — methodology docs, assumption logs, and structured write-ups that others can pick up and run with

Data Scientist – Intelligent Media Planning

Product Manager

• **What Your Day Might Look Like:**
• - Design, develop, and execute proactive, below-the-line targeted campaigns — covering migration, renewal, upsell, and cross-sell — aligned with enterprise mobile commercial objectives.
• - Manage the full campaign lifecycle: audience selection, offer definition, channel strategy, scheduling, and post-campaign evaluation.
• - Help track campaign performance against key metrics (conversion rate, revenue uplift, NPS) and flag optimisation opportunities.
• - Analyse customer datasets to identify behavioural patterns, commercial opportunities, and target populations.
• - Use analytical and data-mining tools (primarily IBM SPSS Modeller) to support segmentation and targeting decisions.
• - Assist in building and refining customer segmentation models as your skills develop.
• - Prepare and maintain regular campaign performance reports and presentations.
• - Support cross-functional teams (Product, Analytics, Sales, Finance, CRM) with data and insight inputs.
• - Translate analytical findings into clear summaries for business stakeholders.