Our talent solution

Data scientists and AI & generative AI

Talent

Data scientists

What our data scientists can do

  • Proficient in building models for regression, time-series forecasting, clustering, and classification, specifically tuned for category dynamics and seasonality in retail environments.
  • Specializes in shopper-focused analytics such as SKU rationalization, basket analysis, promo lift estimation, and long-tail performance.
  • Applies robust statistical tests and model diagnostics to ensure outcomes stand up to commercial scrutiny and drive action.
  • Designs demand forecasting, pricing, and churn models tailored to retailer/brand timelines, balancing accuracy with business usability.
  • Uses ensemble methods, time-aware models, and scenario generators to support decisions around replenishment, promotions, and pricing.
  • Deploys explainable and business-embedded machine learning systems that align with commercial cycles.
  • Extracts structured insights from unstructured inputs like reviews, call transcripts, sales notes, and shopper surveys.
  • Supports brand, R&D, and service teams through topic modeling, sentiment analysis, and summarization models.
  • Combines GenAI and traditional NLP for rapid knowledge synthesis across feedback, Q&A logs, and support channels.
  • Partners with data engineers to align model inputs with retailer, e-Commerce, and internal data structures.
  • Prepares structured datasets from POS, loyalty, syndicated, and e-Commerce feeds for model readiness and auditability.
  • Ensures model outputs are deployed into real systems via APIs, dashboards, or files with refresh automation.
  • Converts complex model outputs into clear visuals and presentations aligned with category, trade, and brand functions.
  • Customizes views by persona—whether a CMO or category analyst—and embeds the story, not just the numbers.
  • Delivers explainable outputs that speed up cross-functional agreement and approval.

Proven impact from our data scientists

Improved forecast accuracy by 23%

Built predictive models for a snack brand that improved accuracy by 23%, reducing stockouts by 18% and increasing on-shelf availability during peak periods. Allowed manufacturing to optimize shift planning and lower costs.

Used price-lift modelling to reallocate budget toward high-performing tactics, eliminating 22% of ineffective promotions. Delivered a 14% boost in ROI for a beverage client across multiple retailers.

Analyzed long-tail SKU performance using contribution margin, velocity, and shopper overlap. Recommended discontinuation of underperforming items, resulting in 12% SKU reduction and 21% increase in shelf productivity.

Developed customer segments and a next-best-offer model integrated into a loyalty app. Drove a 9% increase in average basket value and a 13% rise in repeat trips over 90 days.

What makes our data scientists different

Domain-specific insights:

  • Deep knowledge of category planning cycles, promotional effectiveness, product segmentation, and pack architecture.
  • Models reflect retail realities like distribution voids, competitor cannibalization, and marketing influence.
  • We don’t just model—our data scientists understand the downstream business use of the insight.

Explainable AI & commercial storytelling:

  • Every output includes contextual explanation, visual clarity, and decision-ready packaging.
  • We adapt explanations to the audience, whether it's executive summaries or detailed analyst views.
  • Our narrative capability accelerates buy-in and removes the common 'data gap' barrier to action.

Embedded collaboration across functions:

  • Data scientists work daily with sales, brand, marketing, and supply teamsinstead of working in isolation.
  • Our teams operate in agile, multi-disciplinary pods that are embedded into client workflows.
  • This alignment reduces feedback cycles and ensures what we deliver gets used.

Speed to value through pre-built accelerators:

  • We offer libraries, templates, and pre-configured models designed for CPG and retail use cases.
  • This cuts model build and validation time dramatically and speeds up proof-of-value stages.
  • You start seeing value within weeks, not months.

Talent

AI & generative AI

AI and generative AI capabilities for consumer brands

Generative AI & LLM engineering:
  • Builds and fine-tunes large language models (LLMs) specifically for use cases like marketing copy, sales enablement, chat assistants, and internal knowledge tools.
  • Implements RAG pipelines, custom embeddings, and search-tuned models for domain-specific output generation and knowledge recall.
  • Adds compliance controls and brand guardrails directly into the models, ensuring output consistency across markets and stakeholders.
  • Develops prediction models for pricing, trade spend efficiency, demand planning, shopper churn, and campaign responsiveness.
  • Merges structured (POS, CRM) and unstructured (reviews, call logs) data into unified pipelines powering high-ROI algorithms.
  • Aligns AI logic with business constraints, including promo windows, seasonality, price elasticity, and category-specific rules.
  • Crafts prompts and templates that reflect campaign tone, regulatory requirements, and shopper segments.
  • Creates prompt playbooks for functions like brand marketing, shopper marketing, retail operations for consistent, high-quality reuse.
  • Embeds constraints for regional spelling, phrase rules, brand compliance, and product positioning.
  • Embeds AI outputs into sales systems, TPM tools, planning apps, CRM workflows, and internal portals.
  • Partners with software teams to build end-user tools powered by AI that feel native to the business process.
  • Enables GenAI use without a steep learning curve by focusing on business logic integration.
  • Implements explainability layers, review checkpoints, and human-in-the-loop feedback flows across GenAI touchpoints.
  • Continuously evaluates GenAI performance for bias, factual grounding, brand risk, and regional adaptation.
  • Provides frameworks and training to drive responsible use across commercial, operations, and support teams.

Real GenAI & AI success in the field

Cut campaign content creation time by 80%:

For a cosmetics brand, GenAI produced over 2,000 content variations (product copy, social captions, e-Commerce blurbs) in under 6 hours, reducing manual workload and accelerating campaign readiness. Approval rate: 92%.

Improved forecast accuracy by 24% with generative AI scenarios:

Built a GenAI engine to simulate forecast scenarios (weather, promos, media spikes) and feed them into demand planning. Resulted in 24% better forecast accuracy and improved OTIF by 15%.

Saved 3.5 hours per representative weekly via an AI sales chatbot:

Developed a GenAI assistant using RAG + internal pitch decks, FAQs, and retailer strategy. Reduced pre-meeting prep time from 4 hours to under 30 minutes, freeing up rep capacity for selling.

Increased promotion ROI by 11% using GenAI briefs:

Generated hundreds of promotional playbooks from past data using GenAI. Each brief was tailored to shopper segment, discount structure, and product velocity. Boosted ROI by 11% while reducing promo overlap.

What sets our AI and generative AI experts apart

Built for retail, not just research:
  • Our solutions are tuned to commercial problems such as pricing tiers, content calendars, and category resets, rather than academic benchmarks.
  • Our GenAI systems understand how consumer brands work, from retailer submission rules to voice-of-customer tone.
  • We train models on actual brand assets, guidelines, and sales inputs—not general web data.
  • Guardrails are embedded into every prompt, instruction, and output to ensure the right claims, tone, disclaimers, and phrasing.
  • Content reflects product positioning, region-specific rules, and historical best-performers.
  • Our outputs are so accurate that they pas brand manager review on the first draft 9 out of 10 times.
  • We don’t just build POCs—we deploy working systems used by marketing, shopper, sales, and support teams daily.
  • Includes hosting, feedback capture, prompt libraries, and content monitoring dashboards.
  • We manage uptime, retraining, versioning, and scalability in partnership with your operations and IT teams.
  • We design GenAI workflows that users can understand, approve, and trust without requiring technical literacy.
  • Every solution includes explainers, override options, and confidence scoring.
  • Tools are launched with full onboarding, feedback loops, and change management support.

Get in touch

Our friendly and efficient team is here to discuss your ideas. No pressure, just solutions.

Contact us

What happens next?

  • Our team will reach out to you to schedule a 'no pressure' call to help understand your objectives
  • We'll provide relevant demos and examples. You then confirm to us that you have a formal mandate to purchase.
  • We will provide the best-in-class proposition, tailored to all your nuances.
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