Senior Technical Consultant
Centric Software
- Paris
- CDI
- Temps-plein
- Work closely with project manager and internal team members as well as customers on onboarding projects
- Use insights from business consultant on customer specific processes to ensure all relevant data is being considered/ transformed in order to find the best fitting models for the customers
- End-to-end technical ownership. Being a point of contact for any technical related topics from data engineering & data science about the product.
- Explain complex data engineering or data science related topics to non-technical stakeholders and customers
- Analyze, suggest and prepare AB test setups
- Training of mathematical models in AI/ machine learning and statistical learning that describe the effects of prices and promotions on purchasing behaviour, including behavioural price effects.
- Ensure the accuracy of the models, development of model validation (back-testing) methods to quantify the impact of the solutions on our clients' business.
- Collaboration with product management to generate ideas and quickly turn them into efficient, well-tested, working code (R and Python).
- Ensure all customer specific time & effort is being tracked accurately
- Ensure stable data flow incoming and outgoing
- Interfacing with customers and external partners to align on data formats and transmission schedules.
- Responsible for transforming (normalizing and standardizing) and storing incoming and outgoing data.
- Responsible for documenting the solution architecture for each customer
- A degree in either computer science, data science, mathematics, statistics, physics, or economics or a comparable field.
- Familiarity with relevant topics in mathematics and statistics.
- Familiarity with libraries like Numpy, Pandas, Matplotlib, and Statsmodels; PySpark familiarity is a plus.
- Good SQL skills.
- Excellent communication skills in English, other language is a plus
- 3+ years of hands-on experience in data analytics, ideally in a retail or consumer products space.
- Comfortable analyzing large data sets using tools such as SQL, Python, and R, and are comfortable navigating big data environments.
- Experience with customers and stakeholders and ability to explain highly technical data science-related topics in a language suitable for your audience.