Data Scientist Devi Technologies

Devitechs; Birmingham; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading tech company in Birmingham is seeking a Data Scientist to leverage statistical analysis and machine learning techniques to develop actionable insights. The ideal candidate will have strong programming skills in Python, R, and SQL, and be able to communicate complex data trends effectively. This role involves collaborating with cross-functional teams and designing data visualizations to influence strategic decisions.

Qualifications

• Experience with statistical analysis and machine learning.
• Strong programming skills in Python, R, and SQL.
• Ability to communicate complex insights in simple terms.

Responsibilities

• Identify business problems and design data-driven solutions.
• Build predictive models using machine learning algorithms.
• Analyze data trends to influence company strategy.

Skills

Statistical analysis

Machine learning

Data modeling

Python

R

SQL

Data visualization

Tools

Power BI

Tableau

Job description

A Data Scientist applies statistical analysis, machine learning, and data modeling techniques to uncover actionable insights.

Key Responsibilities:
️ Identify business problems and design data-driven solutions
️ Collect, process, and clean large datasets for modeling
️ Build predictive and prescriptive models using ML algorithms
️ Analyze data trends and patterns to influence strategy
️ Use Python, R, and SQL for data analysis and manipulation
️ Design dashboards and visualizations using Power BI or Tableau
️ Collaborate with cross-functional teams to integrate findings
️ Ensure data integrity and governance throughout the process
️ Develop NLP and computer vision models for advanced analytics
️ Evaluate model accuracy and update based on performance
️ Present insights to stakeholders in non-technical language
️ Implement solutions that improve operational efficiency
️ Apply AI ethics and bias reduction practices
️ Document methodologies, models, and outcomes
️ Contribute to research papers and internal data science initiatives