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We have remote working contract opportunity available for an experienced Data Scientist Consultant to join our global ecommerce client’s Global Tax Technology team.
Your core functions • Support AI/ML model development for Tax technology • Monitor model performance and update/re-train as needed • Develop model success metrics, automate reports for monitoring them • Data Analysis, Visualization and Derive Insights • Maintain a close and pro-active relationship with Engineer team for successful deployment of the model
Skills required
• Excellent technical skills for Machine learning and process development, especially SQL and Python • Experienced in handling big data (Hadoop, Teradata, etc.) • Experience in ML model development and implementation • Proficient in Advanced Excel • Experience with Tableau and other Reporting dashboards • Agile work experience • Ability to translate commercial requirements into software solutions • Capable to work independently Basic Qualifications: • 8-10 years’ hands-on experience in data analytics • Proven knowledge in SQL coding and Python programming
Some details on the day-day work: 1. Monitoring performance of live models (i.e. models already live on the site) a. Excellent reporting skills, build automated reports that can be refreshed ad-hoc or scheduled b. Identify the key metrics needed for model monitoring c. Check if there is variation in accuracy and other key metrics, and find impact /root cause if accuracy is dropping d. identify next steps and communicate to business 2. Regular update of existing models using recent data, or re-training when there are business changes 3. Build new model for new countries a. Data preparation b. Category mappings done with the help from BU (but this person to initiate and co-ordinate this) c. Data upload to Vertex server (cloud environment. No separate skills or Azure knowledge required for this part. This can be picked up easily) d. Train/Test models using Lucy algorithm e. Important part – Model assessment, distinguish categories doing well vs not based on pre-decided metrics f. Create the report, next steps for model improvement where needed, and communicate well to stakeholders g. Model improvement could include – further data cleansing/ manipulation/ transformations, or even trying new techniques/algorithms for the low performing categories 4. Co-ordinating with Engineering teams for getting the models into production. a. Need to be able to communicate well/explain the details and hand over models to Engineering team Also, ensure Engg. process of Datawarehouse updates etc. (on live model results) works for us as we need that data for Reporting Role: Data Scientist - SQL/Python Job Type: Contract Location: London, London,