About the Role
At Trustpilot, our Data Scientists in the GTM Applied AI team leverage an extensive dataset to build AI/ML models that improve go-to-market (GTM) efficiency and enhance pricing and revenue management strategy. We are seeking a skilled Data Scientist to join this team, focusing on developing, deploying, and maintaining our GTM and Pricing models. You will work closely with our pricing and monetization squad, software developers, data analysts, and ML engineers to develop and deploy innovative AI/ML models at scale. This role offers the opportunity to collaborate broadly across the business, including with our Commercial, Digital Sales, and Applied AI teams, in both B2B and B2C contexts. This is a Fixed-Term Contract (FTC) for a duration of 12 months.
What you’ll be doing:
- Involved in delivering key Data Science projects aimed at improving GTM efficiency and pricing practices, covering areas from prediction to ranking, segmentation to NLP, and recommendation systems to content generation.
- Deliver the Data Science component of strategic initiatives, including owning, maintaining, and deploying production-ready ML/AI models, and analyzing data to establish the scope and impact of your work.
- Identify new pricing and monetization opportunities based on data, interpret model outcomes, and share insights to drive business goals.
- Engage with both technical and non-technical stakeholders, translating business requirements into Data Science deliverables.
- Work with leading data engineering technologies, including Google Vertex AI tools, Google BigQuery, BigQuery Pipelines, and Airflow, alongside leading Data Science tools and emerging technologies for model building and deployment.
- Develop your career in a friendly, diverse, innovative, international team and workplace.
Who you are:
- Experience with analytical and quantitative problem solving using advanced statistical techniques and machine learning methods, such as Attribution, Segmentation, Churn, Upgrade, Upsell, Pricing Optimisation, and LTV.
- Experience in building and deploying production-ready ML models, coupled with solid data engineering skills (e.g., experience with cloud technologies like GCP; experience with AWS is also relevant).
- Proficiency in Python and SQL for data manipulation, modeling, and scripting.
- Experience working with large datasets. Knowledge of data generated by websites or in the e-commerce sector, behavioral analytics, and experience working with data from commercial systems (e.g., Salesforce) is advantageous.
- Knowledge of data pipelining and prior experience with cloud-based ML model deployments are beneficial.
- Great communication skills, for both technical colleagues and business stakeholders.
- Proven technical experience in a Data Science role, particularly within the technology sector or a technical consultancy.