- Company Name
- Datatech Analytics
- Job Title
- Data Scientist - Customer Data
- Job Description
-
**Job Title**
Data Scientist – Customer Data
**Role Summary**
Lead the design, development, and deployment of predictive analytics solutions focused on customer behaviour and segmentation. Translate large volumes of transactional, behavioural, and demographic data into actionable insights that drive CRM initiatives and personalized customer experiences across channels.
**Expectations**
- Hold full UK work rights; no sponsorship required.
- Strong leadership and cross‑functional collaboration skills.
- Ability to manage end‑to‑end lifecycle of data science projects from model conception to production deployment.
**Key Responsibilities**
1. Build and deploy predictive models (supervised, unsupervised, NLP, Bayesian, time‑series, collaborative filtering) to identify drivers of purchase patterns, customer lifetime value, and sentiment.
2. Create advanced customer segmentation using behavioural, transactional, and demographic data.
3. Design model validation and A/B test frameworks to evaluate CRM initiatives.
4. Transform analytical prototypes into production‑ready code; integrate models into existing stack.
5. Maintain and optimise model performance through continuous monitoring, retraining pipelines, and ML Ops practices.
6. Communicate findings through clear visualisations and written reports to stakeholders across marketing, CRM, and engineering.
7. Provide data‑driven recommendations to improve engagement metrics and personalise customer experiences.
**Required Skills**
- Applied statistics and machine learning (supervised/unsupervised, NLP, Bayesian, forecasting, collaborative filtering).
- Proficient in Python; experienced with pandas, numpy, scipy, scikit‑learn, tensorflow/pytorch.
- Knowledge of cloud platforms (GCP, AWS, Azure) and data‑science tools (Dataiku, Databricks).
- Experience with ML Ops: model deployment, monitoring, and retraining pipelines.
- Excellent written and verbal communication; ability to translate technical insights into business value.
- Comfortable working in a global or multi‑regional environment (preferred).
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related field.
- Professional certifications (e.g., Google Cloud Professional ML Engineer, AWS Certified Machine Learning – optional).