RQ09863 Data Science Developer Intermediate

Responsibilities:

• Participate in product teams to analyze systems requirements architect design code and implement cloud-based data and analytics products that conform to standards.
  
• Design create and maintain cloud-based data lake and lakehouse structures automated data pipelines analytics models and visualizations (dashboards and reports).
  
• Liaises with cluster IT colleagues to implement products conduct reviews resolve operational problems and support business partners in effective use of cloud-based data and analytics products.
  
• Analyses complex technical issues identifies alternatives and recommends solutions. Prepare and conduct knowledge transfer
  

General Skills:

• Experience in multiple cloud base data and analytics platforms and coding/programming/scripting tools to create maintain support and operate cloud-based data and analytics products.
  
• Experience with designing creating and maintaining cloud-based data lake and lakehouse structures automated data pipelines analytics models and visualizations (dashboards and reporting) in real world implementations
  
• Experience in assessing client information technology needs and objectives
  
• Experience in problem-solving to resolve complex multi-component failures
  
• Experience in preparing knowledge transfer documentation and conducting knowledge transfer
  
• A team player with a track record for meeting deadlines
  

Desirable Skills:

• Written and oral communication skills to participate in team meetings write/edit systems documentation prepare and present written reports on findings/alternate solutions develop guidelines / best practices Interpersonal skills to explain and discuss advantages and disadvantages of various approaches
  
• Experience in conducting knowledge transfer sessions and building documentation for technical staff related to architecting designing and implementing end to end data and analytics products Technology Stack Azure Storage Azure Data Lake Azure Databricks Lakehouse and Azure Synapse Python SQL Azure Databricks and Azure Data Factory Power BI
  

Requirements

Experience and Skill Set Requirements:

Must Haves:

• 25 years of professional experience in data science data analytics or a related quantitative field (e.g. data engineering machine learning or business intelligence) or equivalent.
  
• Proven experience in data analysis visualization and statistical modeling for real-world business or research problems.
  
• Demonstrated ability to clean transform and manage large datasets using Python R or SQL.
  
• Programming & Data Handling
  
• Python (pandas NumPy scikit-learn statsmodels matplotlib seaborn)
  
• SQL (complex queries joins aggregations optimization)
  
• Data preprocessing (feature engineering missing data handling outlier detection)
  
• Experience working with big data frameworks such as Apache Spark and Hadoop for large-scale data processing.
  

Skill Set Requirements:

Experience:

• 25 years of professional experience in data science data analytics or a related quantitative field (e.g. data engineering machine learning or business intelligence) or equivalent.
  
• Proven experience in data analysis visualization and statistical modeling for real-world business or research problems.
  
• Demonstrated ability to clean transform and manage large datasets using Python R or SQL.
  
• Hands-on experience building and deploying predictive models or machine learning solutions in production or business environments.
  
• Experience with data storytelling and communicating analytical insights to non-technical stakeholders.
  
• Exposure to cloud environments (AWS Azure or GCP) and version control tools (e.g. Git).
  
• Experience working in collaborative cross-functional teams ideally within Agile or iterative project structures.
  
• Knowledge of ETL pipelines APIs or automated data workflows is an asset.
  
• Previous work with dashboarding tools (Power BI Tableau or Looker) is preferred.
  

Technical Skills:

• Programming & Data Handling
  
• Python (pandas NumPy scikit-learn statsmodels matplotlib seaborn)
  
• SQL (complex queries joins aggregations optimization)
  
• Data preprocessing (feature engineering missing data handling outlier detection)
  

Machine Learning & Statistical Modeling:

• Proficiency in supervised and unsupervised learning techniques (regression classification clustering dimensionality reduction)
  
• Understanding of model evaluation metrics and validation techniques (cross-validation A/B testing ROC-AUC confusion matrix)
  
• Basic understanding of deep learning frameworks (TensorFlow PyTorch or Keras) is a plus
  

Data Visualization & Reporting:

• Expertise with visualization libraries (matplotlib seaborn plotly or equivalent)
  
• Experience building interactive dashboards (Tableau Power BI Dash or Streamlit)
  
• Ability to design clear impactful data narratives and reports
  

Data Infrastructure & Tools:

• Experience with cloud-based data services (e.g. AWS S3 Redshift Azure Data Lake GCP BigQuery)
  
• Experience working with big data frameworks such as Apache Spark and Hadoop for large-scale data processing.
  
• Familiarity with data pipeline and workflow tools
  
• Experience with API integration and data automation scripts (Selenium Python etc)
  
• Solid grounding in probability statistics and linear algebra
  
• Understanding of hypothesis testing confidence intervals and sampling methods
  

Soft Skills:

• Strong communication skills; both written and verbal
  
• Ability to develop and present new ideas and conceptualize new approaches and solutions
  
• Excellent interpersonal relations and demonstrated ability to work with others effectively in teams
  
• Demonstrated ability to work with functional and technical teams Demonstrated ability to participate in a large team and work closely with other individual team members
  
• Proven analytical skills and systematic problem solving
  
• Strong ability to work under pressure work with aggressive timelines and be adaptive to change
  
• Displays problem-solving and analytical skills using them to resolve technical problems
  

Public sector Experience:

• OPS(or other government) standards and processes