Data Scientist - Pre-Sales (F/M/X)

Posted 5 Days Ago
Be an Early Applicant
Hiring Remotely in DE
Remote
Mid level
Cloud • Software • Consulting
The Role
As a Data Scientist in Pre-Sales, you will implement data-driven solutions, support sales with analytics expertise, and collaborate with technical teams on AI and machine learning projects.
Summary Generated by Built In

Welcome to an exciting opportunity where ambitious individuals are invited to join a team of inquisitive minds and supportive peers, all driven by a shared passion and diverse skills aimed at creating value for businesses through data!

  
About Us      

Ascent has recently been acquired by Acuity Analytics.  This is both a significant milestone for us and a tremendous opportunity for you.  Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans.  We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations.  To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency.  

   

Your responsibilities  

As our next Data Scientist (F/M/X) you take care of implementing data-driven solutions together with other data scientists, data engineers and the client’s technical team:   

  • Support the sales team with data science and analytics expertise throughout the sales cycle
  • Act as a technical advisor for customers, understanding their business challenges and translating them into data-driven solutions
  • Design, build, and present data science use cases, demos, and proof-of-concepts (PoCs) tailored to customer needs
  • Implementation of proof of concepts in AI, data science, and machine learning   
  • Data preparation, model implementation, and development of productionizable high-quality code in Python are your daily business  
  • Close collaboration with your team members in the conception of data science and AI solutions for our clients  
  • Assisting in workshops with the client’s team  
  • You will work in different industries on various data science and AI use-cases  

Skills and experience  

  • You have an educational background in the field of Mathematics, Computer Science, Data Science, Statistics or similar   
  • Knowledge in implementing machine learning pipelines in either Python or R with proficiency of the respective libraries (caret, dplyr, tidyverse or scikit-learn, pandas, numpy etc.) is required  
  • Solid understanding of statistics and mathematics  
  • Experience in working on GenAI related projects (e.g. with langchain, chainlit, RAG, LLMs)  
  • Nice-to-have: Experience with cloud-based environments or advanced technologies like Spark, Tensorflow or Keras  
  • Motivation and passion for learning new things and honing your skills  
  • You are fluent in both German and English  
 

Why join us?

People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.  Check out this page for more details.

Top Skills

Caret
Chainlit
Dplyr
Keras
Langchain
Llms
Numpy
Pandas
Python
R
Rag
Scikit-Learn
Spark
TensorFlow
Tidyverse
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The Company
London
452 Employees
Year Founded: 2005

What We Do

Ascent is a design-led software, data and cloud business that specialises in advanced analytics and AI. We design, build and manage cloud-native products, solutions, platforms and experiences on Azure. Our community of engineers, architects, data scientists, experience designers and consultants is here to help customers do something new, or do something better. Ascent is home to 450+ technology specialists across 5 key European locations (UK, Germany, Portugal, Malta and Bulgaria). Our talented, consultative teams deliver a range of solutions, from digital product and service design to mobile app development, API integrations, data engineering, AI and data science. Our modern app, data and infrastructure platforms help businesses leave legacy behind and enable rapid, efficient innovation

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