Senior Data Scientist (Machine Learning & NLP)

Acuity
United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Agile Methodology Data Analysis Big Data Computer Programming Decision Support Systems Python (Programming Language) Machine Learning Natural Language Processing Search Technologies Cloud Platform System Apache Spark
+4 more
Model Validation Machine Learning Operations Software Library Databricks

Job description

We are looking for an experienced Senior Data Scientist to design, build, and optimise intelligent recommendation and ranking solutions that drive better customer outcomes.

Working as part of a collaborative data and engineering team, you will develop production-ready machine learning models, leverage behavioural analytics, and apply modern NLP techniques to solve complex business challenges. You’ll work with large-scale datasets using Databricks and Spark, taking models from experimentation through to deployment while continuously improving live system performance.

This is an exciting opportunity for someone who enjoys solving real-world problems and building scalable machine learning solutions that deliver measurable business impact., * Design, build, and deploy machine learning models for recommendation and ranking systems.

  • Analyse behavioural data to identify patterns and opportunities for optimisation.
  • Develop NLP solutions to enhance intelligent matching and search capabilities.
  • Build scalable machine learning pipelines using Databricks and Spark.
  • Design, execute, and evaluate product experiments to improve model performance.
  • Monitor, optimise, and continuously improve production machine learning models.
  • Collaborate with Data Scientists, Data Engineers, Product Managers, and stakeholders to deliver high-impact solutions.
  • Apply statistical techniques to evaluate model effectiveness and support data-driven decision making.

Requirements

  • Strong commercial experience in Machine Learning and predictive modelling.
  • Experience with behavioural analytics and user behaviour modelling.
  • Hands-on experience with Natural Language Processing (NLP).
  • Strong experience using Databricks and Apache Spark.
  • Experience building recommendation or ranking systems.
  • Strong knowledge of statistical modelling and model evaluation techniques.
  • Experience designing and analysing product experimentation (A/B testing and experimentation frameworks).
  • Strong programming skills in Python and experience working with machine learning libraries.
  • Experience working with large datasets and developing scalable ML solutions.

Soft skills

  • Strong analytical and problem-solving skills.
  • Ability to communicate technical concepts to both technical and non-technical stakeholders.
  • Collaborative approach with experience working in cross-functional Agile teams.
  • Passion for building production-quality machine learning solutions.
  • Ability to balance experimentation with delivering measurable business value., * Experience building production-grade recommendation or matching systems within industries such as e-commerce, marketplaces, recruitment, property, or financial services.
  • Experience improving live matching performance rather than developing research prototypes.
  • Experience deploying and monitoring machine learning models in cloud environments.
  • Familiarity with MLOps principles and model lifecycle management.

About the company

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.

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