Predict growth. Automate decisions. Turn your data into momentum.
I use data science to drive real growth, not vanity dashboards. From predictive LTV and churn modelling to product led onboarding flows, pricing automation and audience targeting, I build systems that connect your data directly to the levers that grow your business. These are not just models, they're decision engines: they power dynamic pricing, trigger lifecycle campaigns, score leads, cluster behaviours and forecast revenue in ways no static report can.
Every signal is actionable, every insight is tied to outcome. Whether you're scaling a SaaS platform or optimising an eCommerce funnel, I turn your raw data into a compounding advantage, owned, production ready, and deeply integrated with your stack.
No guesswork. No lag. Just data that acts.
competitor_scraper.py
⇣ Predicted LTV from real usage data
Predicted LTV Actions
Based on behaviour, recency and product usage
| Customer | Segment | Predicted LTV | Recommended Action |
|---|---|---|---|
| C. Lopez | Power user | £1,850 | Offer annual plan |
| R. Singh | At risk | £120 | Trigger win-back email |
| T. Anders | New user | £480 | Wait and observe |
From Insight to Action
Core Data Science Benefits That Move the Needle
These are not just models or metrics. They are growth levers, deeply embedded into your product, marketing and pricing. From better segmentation and real time decisioning to churn prediction and LTV forecasting, I use data science to automate what used to be guesswork and expose what used to be invisible. Every insight is engineered to drive action, every model tuned for business impact.
- Smarter segmentation
Unlock more valuable audiences with intelligent clustering and scoring. Know who is ready to upgrade, who will convert with the right nudge, and who is worth reactivating.
- Customer journey analytics
See the complete path to conversion, and where it breaks. I track and model drop off points, time to value, activation friction and funnel bottlenecks with clarity.
- Automated decision making
Data that sits in a dashboard is wasted. I build systems that act, triggering campaigns, pricing changes or product nudges the moment the data says they should.
- Attribution clarity
Stop guessing what worked. I use probabilistic models and behavioural data to reveal which touchpoints actually drive conversions and retention, across channels.
- Dynamic bidding and offer logic
React in real time to market signals. Whether it's Google Ads, product feeds or on site offers, I optimise your decisions based on competition, demand and performance.
- Churn prevention and recovery
Spot users at risk of leaving before they do. My models trigger personalised retention flows, reactivation sequences or even product interventions to win them back.
- Product led insights
Understand what really keeps users around. I map feature usage to retention and upgrades, giving your product team direction grounded in real behaviour.
- Revenue forecasting
No more spreadsheets. I use cohort based models to predict MRR growth, CAC payback, LTV by segment and other critical growth metrics, with confidence intervals, not gut feeling.
Data Science for Growth
From Raw Signals to Revenue
This is the pipeline that turns your product and marketing data into measurable, automated outcomes. Every signal becomes a trigger, every model drives an action, and every part of your stack learns as it grows.
Marketing Personalisation
Triggered offers, behavioural flows, adaptive messaging
Campaign Automation
Pricing changes, ads, CRM sync, smart scheduling
The Whole Journey
From first click to confident decision
Data science is not a report at the end of the quarter. It is a pipeline that runs every day, and it only works if every stage is built properly. This is the arc I build for ecommerce stores, for Regios, for every client, designed on day one so the figures are simply there the moment you need them.
Track
A tracking strategy, not a pixel dropped on a page. Every touchpoint planned.
Collect
Events from shop, ads, emails and CRM land in one place, structured.
Clean
Duplicates merged, gaps filled, formats fixed. Rubbish in stays out.
Understand
Insights in plain language, not a wall of numbers.
Decide
Statistics with error margins, so you know when to act.
Forecast
Models that look ahead, so you plan instead of react.
Because the architecture exists from day one, no time is ever wasted rebuilding history. Whatever question comes next, the data to answer it is already flowing.
Collect & Clean
Your data is messier than you think. That is fixable.
Every real dataset arrives with duplicates, typos, missing fields and seventeen ways of writing the same city. Models built on mess produce confident nonsense. So before anything clever happens, the data gets cleaned, automatically, every single day.
What arrives
What the models see
Merged, completed, validated. Automatically, nightly, with an audit trail.
Understand
Insights, not table dumps
Most agency reporting is impressions, clicks and cost per click: about as useful as chopsticks with a steak. A proper analyst gets you to real revenue numbers, but still leaves you alone with a table. Real analysis ends in a sentence you can act on. Watch the same story climb all three steps.
What most agencies send
| Channel | Impr. | Clicks | CPC | Spend |
|---|---|---|---|---|
| Google Ads | 412k | 12,480 | €0.62 | €7.7k |
| 986k | 9,870 | €0.48 | €4.7k | |
| TikTok | 1.2m | 5,660 | €0.35 | €2.0k |
| Display | 2.3m | 3,140 | €0.19 | €597 |
| YouTube | 764k | 1,890 | €0.41 | €775 |
Millions of impressions. Not one number about money coming back.
What a good analyst sends
| Channel | Orders | CR | Revenue |
|---|---|---|---|
| Google Ads | 312 | 2.5% | €18,140 |
| Comparison sites | 158 | 4.9% | €21,020 |
| SEO | 224 | 2.8% | €15,930 |
| Direct | 201 | 2.9% | €14,880 |
| Newsletter | 171 | 3.8% | €12,270 |
| 118 | 1.2% | €6,410 | |
| Referral | 64 | 3.2% | €5,470 |
| TikTok | 45 | 0.8% | €2,210 |
412 rows closer to the truth. Still no decision.
What you get from me
The same data, understood
Customers arriving through comparison sites spend 2.3x more over their first year than social traffic, but get only 12% of the ad budget.
Recommendation: shift €1,800 per month and measure for six weeks.
Decide
Decisions with an error margin, not a gut feeling
Two campaign variants, one looks better. Is it real or is it luck? Statistics answers that question with a number. Early on, the uncertainty ranges overlap: acting now would be gambling. With enough data they separate, and the decision makes itself.
After 500 visitors
Variant A: 3.6% ± 1.6
Variant B: 4.4% ± 1.7
Ranges overlap. Could be luck. Keep testing.
After 4,800 visitors
Variant A: 3.7% ± 0.4
Variant B: 5.1% ± 0.5
97% confident B wins. Act.
Every Number Has A Range
A conversion rate is never just 4.2%. It is 4.2% plus or minus something, and that something decides whether you should care.
Known Error Margins
Decisions come with their uncertainty attached: act at 95% confidence, wait below it. No premature champagne, no missed winners.
Tests That End
Defined sample sizes and stopping rules, so experiments produce verdicts instead of running forever.
Forecast
Forecasting: the part that changes how you run the business
A good forecast turns management from reactive to deliberate. Different industries need different models: retail lives on seasonality, SaaS compounds, energy follows the weather. Pick your world below and see what the model has to understand.
Retail forecasting is seasonality first: weekly rhythm, promotion spikes and the December wave. Stock, staff and ad budget get planned against the curve, not against hope.
Models Per Industry
Seasonality, trend, promotions, churn, weather: whatever actually drives your numbers is what the model is built around. No one size fits all.
Plan With Confidence
Management sees an honest range months ahead: stock, hiring, cash flow and campaigns planned against the curve instead of last quarter.
Budgets From Forecasts
When you know what a month will bring, ad budgets stop being a guess. Spend rises into strong periods and pulls back before soft ones.
Marketing, Finally Measured
Against a modelled baseline, performance marketing shows its true added value week by week, instead of claiming credit for sales that would have happened anyway.
Automation & Dashboards
The right numbers for every level, updated by themselves
Nobody should export a spreadsheet to know how the business is doing. Dashboards run automatically and every level sees exactly what it needs: the board gets the big picture, management steers, operations acts. Everything is live around the clock, nothing is compiled by hand. Built exactly this way for Stint in London and for Regios.
Three numbers and a direction. Enough to govern, nothing to drown in.
Revenue vs forecast
+7.2%
Health index
78 / 100
Runway effect
+2.1 months
Real Time, Any Time
No month end wait, no PDF arriving two weeks late. Open the dashboard at 7am or 11pm and the numbers are current, because they update themselves.
Not 30% Of Your Retainer
Classic agency reporting is put together by hand and quietly eats up to a third of the retainer. Here reporting is software: it builds itself every night, and that budget goes into actual work.
The Right Story Per Role
C level, management, executives and analysts each get their own view of the same data, delivered at the altitude that role actually works at.
The Engineering Behind It
Real code, not spreadsheet magic
All of this is built in Python with the standard scientific stack, engineered like software because it is software: versioned, tested and running on a schedule, not living in a notebook on somebody’s laptop.
python · the stack
✓ pandas # data wrangling and cleaning
✓ scikit-learn # models and validation
✓ statsmodels & Prophet # forecasting and seasonality
✓ NumPy & SciPy # the numerical engine
✓ Matplotlib & Plotly # visuals humans understand
Versioned & Tested
Analysis code lives in git with tests, like every other part of your product. Results are reproducible, not one off miracles.
Pipelines, Not Rituals
Collection, cleaning, modelling and dashboards run automatically, nightly. Nobody has to remember anything.
Wired Into Your Product
Models talk to your Rails app, your shop and your dashboards through clean APIs, the same architecture GrowCentric.ai runs on.
Your Stack, Versioned, Validated and Battle Tested
Behind every personalised experience or automated campaign is a serious stack, pipelines, models, infrastructure, and tracking layers that need to be clean, reproducible and production safe. I build with the same tools and practices used in high performing teams: notebooks that ship to production, models that self monitor, and pipelines that hold up to scrutiny. Whether you're a solo founder or have your own data team, this work integrates seamlessly into your workflow.
- Data pipeline orchestration
- Airflow, Dagster, dbt or fully custom Python jobs, orchestrated for reliability, observability and long term maintainability.
- Modelling and evaluation
- LTV, churn, segmentation and regression models using XGBoost, CatBoost, sklearn, scored with proper validation and tracked over time.
- Tracking and identity stitching
- Server side events, cookie less identifiers and anonymous to known user resolution built directly into your backend stack.
- ETL/ELT infrastructure
- BigQuery, Snowflake, Postgres, Fivetran, Segment. I integrate the tools that work best for your team and make sure the data flows cleanly.
- Reproducibility and versioning
- Model version control, MLflow tracking, git based pipelines and structured feature stores for consistent and auditable results.
- Notebook to production flow
- Convert exploratory Jupyter notebooks into production safe API endpoints used in your app, CRM or internal tools.
- Privacy aware workflows
- All data flows are consent first and GDPR compliant. From hashed IDs to compliant logging and pseudonymisation, privacy is built in.
Serious Growth Starts with Serious Data Infrastructure.
If you're tired of hacks, dashboards and duct tape, I'll help you build a durable foundation that scales cleanly.
1%of every invoice goes to a UK charity you pick.
A donation, never sponsorship. You choose the cause at onboarding.
The story behind the pledge →