Role – Data Scientist JD
Key Responsibilities
- Partner with business stakeholders to identify and prioritise opportunities where data science can deliver measurable value.
- Collect, clean, and transform structured and unstructured data from multiple internal and external sources.
- Develop, test, and deploy predictive models and machine learning algorithms to address business challenges.
- Conduct exploratory data analysis (EDA) to uncover trends, patterns, anomalies, and key drivers.
- Communicate insights and recommendations through clear storytelling, visualisations, and dashboards.
- Collaborate with engineering teams to productionise models and ensure reliability, scalability, and ongoing performance.
- Evaluate model accuracy and effectiveness, implementing continuous optimisation and tuning.
- Stay up to date with emerging data science tools, methodologies, and industry best practices.
- Perform sensitivity analysis to assess model robustness and variable impact.
Required Skills and Qualifications
- At least 5 years’ experience in client‑facing data science roles with demonstrable impact on business outcomes.
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
- Strong proficiency in Python or R, including libraries such as pandas, scikit‑learn, NumPy, TensorFlow, or PyTorch.
- Solid understanding of statistical analysis, hypothesis testing, and experimental design.
- Hands‑on experience applying a range of supervised and unsupervised machine learning techniques (e.g., Random Forest, regression models, clustering methods).
- Proficiency with SQL and data warehousing technologies.
- Ability to translate complex analytical findings into clear, practical business recommendations.
- Strong problem‑solving skills and natural curiosity for exploring and understanding data.
Preferred Skills and Qualifications
- Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
- Background in deploying machine learning models into production environments (MLOps experience is advantageous).
- Hands‑on experience with big‑data or distributed computing tools such as Spark or Databricks.
- Familiarity with visualisation tools such as Power BI, Tableau, or Plotly.
- Industry experience in sectors such as retail, finance, healthcare, or similar (customisable).
Key Competencies
- Strong analytical and conceptual thinking.
- Excellent communication and data‑storytelling capabilities.
- Effective collaboration and stakeholder‑engagement skills.
- High attention to detail and commitment to data accuracy.
Continuous learning mindset and openness to new techniques and technologies
hackajob is partnering with NTT DATA UK to fill this position. Create a profile to be automatically considered for this role—and others that match your experience.
