We are a management consulting firm resting on three oars - People, Systems & Technology. At psyntech, we understand current trends as they occur across industries and as such, our clients can rely on receiving innovative, well tailored, contextual & practical solutions to their business needs.
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.
Method of Application
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