Data Scientist & Business Intelligence Reporting Specialist at Psyntech Limited

Key Responsibilities

Data Science & Advanced Analytics

• Collaborate with stakeholders to identify and prioritize opportunities for leveraging data to solve complex business challenges.
• Mine, clean, and analyze large datasets from multiple sources to uncover trends, patterns, and optimization opportunities.
• Build, validate, and deploy predictive models, machine learning algorithms, and statistical analysis to optimize customer experience, revenue generation, and operational processes.
• Develop, implement, and maintain custom algorithms, simulation models, and forecasting tools.
• Design and manage A/B testing frameworks, evaluating results to refine business strategies.
• Research and assess new data sources, ensuring integrity, accuracy, and relevance for analytics initiatives.

Business Intelligence & Reporting

• Develop and maintain interactive dashboards, reports, and visualizations using BI tools (e.g., Power BI, Tableau, Qlik, or Looker).
• Translate complex analytical findings into clear, actionable insights for non-technical stakeholders and executive leadership.
• Create automated reporting pipelines to ensure timely delivery of key metrics.
• Monitor data quality, integrity, and governance in BI environments.
• Partner with cross-functional teams to define and track KPIs, performance metrics, and success criteria for projects.

Qualifications & Skills

Essential:

• Degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
• 5–7 years of experience in data science, statistical modeling, and BI reporting.
• Advanced proficiency in statistical computer languages (e.g., Python, R, SQL) for data manipulation and analysis.
• Strong knowledge of machine learning techniques (e.g., regression, classification, clustering, neural networks, decision trees) and statistical methods (e.g., hypothesis testing, probability distributions).
• Proven experience in BI tools (Power BI, Tableau, Qlik, etc.) and data visualization best practices.
• Strong database querying skills (SQL, MySQL, PostgreSQL) and experience with distributed data tools (Hadoop, Hive, Spark).
• Familiarity with cloud data environments (AWS Redshift/S3, Azure Synapse, Google BigQuery).
• Excellent communication skills, with the ability to present complex data findings clearly to non-technical audiences.

Preferred:

• Experience with version control systems (Git/GitHub).
• Familiarity with APIs, web scraping, and integration of external data sources.
• Knowledge of advanced analytics environments (Gurobi, MATLAB, SAS).
• Understanding of data governance, compliance, and security best practices.
• Experience with 3rd party analytics tools (Google Analytics, Facebook Insights, Adobe Analytics).

Core Competencies

• Analytical Thinking: Ability to approach problems logically and make data-driven decisions.
• Business Acumen: Understands how data insights impact revenue, cost, and operational efficiency.
• Collaboration: Works effectively across departments with varying technical backgrounds.
• Adaptability: Stays ahead of emerging analytics and BI technologies.
• Innovation: Proactively identifies opportunities to enhance processes, products, and services using data.

Performance Metrics

• Accuracy, reliability, and adoption rate of developed models and BI dashboards.
• Measurable impact of analytics initiatives on revenue, cost savings, and efficiency.
• Stakeholder satisfaction with the quality and timeliness of insights delivered.
• Reduction in manual reporting through automation.