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Senior Data Scientist
Solirius Consulting. Design, develop, and deploy machine learning and AI models, including predictive models, NLP, computer vision, and recommender systems .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, developing, and deploying machine learning and AI models, with a strong focus on predictive modeling, NLP, and computer vision. Proficient in building scalable data pipelines and integrating models into production systems while effectively communicating insights to diverse stakeholders.
Highest-signal resume keywords
Machine Learning ExpertisePython ProficiencyCloud Platform ExperienceMLOps KnowledgeStatistical Analysis Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData SciencePredictive ModelingFeature EngineeringModel EvaluationStatistical AnalysisNLPComputer VisionRecommender SystemsPrompt Engineering
Soft Skills
Effective CommunicationCollaboration
Tools & Technologies
PandasNumPyScikit-learnTensorFlowPyTorchAWSAzureGCPMLflowKubeflow
Industry Keywords
Data PipelinesModel DeploymentContinuous ImprovementLarge DatasetsGenerative AI
Tech Stack
Tools & technologiesAirflowAWSAzureCloudGoogle Cloud PlatformNoSQLNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Design, develop, and deploy machine learning and AI models, including predictive models, NLP, computer vision, and recommender systems
- Explore, cleanse, and transform large structured and unstructured datasets
- Conduct statistical analysis, experiment design, feature engineering, and model evaluation
- Build scalable data pipelines and automate model training and inference processes
- Collaborate with engineering teams to integrate models into production systems
- Monitor model performance, detect drift, and implement continuous improvement strategies
- Communicate complex findings clearly to technical and non-technical stakeholders
- Stay current with advancements in AI/ML, including LLMs, generative AI, and reinforcement learning, and evaluate their potential impact on products
- Collaborate with product, engineering, and business teams to transform data into actionable insights and high-impact AI solutions
Requirements
What you’ll need- Experience in machine learning, data science, or applied AI roles
- Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch)
- Strong understanding of statistics, ML algorithms, and model evaluation techniques
- Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines
- Ability to analyse large datasets and communicate insights effectively
- Experience with LLMs, generative AI, and prompt engineering
- Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow)
- Familiarity with SQL, NoSQL, and distributed data technologies
- Experience deploying AI models in production environments
- Publications, patents, or open-source contributions in ML/AI
Benefits
Comp & perks- Competitive Salary
- Bonus Scheme
- Private Healthcare Insurance
- 25 Days Annual Leave + Bank Holidays
- Up to 10 days allocated for development training per year
- Enhanced Parental Leave
- Paid Fertility Leave (5 Days)
- Contributory Pension
- EAP with Help@Hand
- Gym Membership Benefits
- Flexible Benefits Allowance
- Cycle to Work and Electric Vehicle schemes
- Flexible Working
- Annual Away Days/Company Socials
- Gender diversity group
- Mental health and wellbeing support
- Reasonable adjustments to support the application process