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Predictive Analytics Manager
1 month ago
Key Responsibilities:
Team Leadership & Management: Lead, mentor, and manage a team of data scientists, analysts, and modelers, fostering a collaborative and results-driven culture.
Predictive Modeling: Develop, implement, and optimize predictive models to analyze trends, behaviors, and outcomes. Utilize techniques such as machine learning, statistical analysis, and time-series forecasting.
Data Strategy & Insights: Work with cross-functional teams to identify business challenges, translate them into analytical problems, and create actionable insights. Provide data-driven recommendations that support strategic decision-making.
Stakeholder Collaboration: Engage with business leaders and departments (e.g., marketing, finance, operations) to understand objectives and tailor analytics solutions to meet their needs.
Data Quality & Integrity: Ensure the accuracy, completeness, and consistency of data used for predictive modeling. Implement best practices for data governance.
Technology & Tools: Stay updated on industry trends, best practices, and emerging technologies related to predictive analytics, and ensure the use of cutting-edge tools and platforms.
Reporting & Visualization: Translate complex data into clear, actionable insights through reports, dashboards, and visualizations to communicate findings to both technical and non-technical stakeholders.
Continuous Improvement: Continuously evaluate and improve predictive models to ensure they remain relevant and effective as business needs evolve.
Key Qualifications:
Education: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related field. PhD is a plus.
Experience:
5+ years of experience in predictive analytics, data science, or related fields, with at least 2 years in a leadership or management role.
Proven experience in building and deploying predictive models using techniques such as regression analysis, machine learning, and time-series forecasting.
Familiarity with advanced statistical techniques and algorithms.
Technical Skills:
Strong proficiency in programming languages such as Python, R, or SQL.
Hands-on experience with data analysis tools and platforms like SAS, SPSS, or similar software.
Experience with data visualization tools (e.g., Tableau, Power BI) and big data platforms (e.g., Hadoop, Spark) is a plus.
Knowledge of cloud platforms (e.g., AWS, Azure) is advantageous.
Analytical Skills: Exceptional problem-solving abilities, with a track record of using data to drive business outcomes.
Leadership Skills: Experience in managing and mentoring a team, with strong interpersonal and communication skills to collaborate effectively with diverse teams.
Business Acumen: Ability to translate complex analytical concepts into business strategies and insights.
Communication Skills: Ability to clearly communicate complex analyses to both technical and non-technical audiences.
Preferred Qualifications:
Experience in industries such as finance, healthcare, e-commerce, or telecommunications.
Certification in data science, machine learning, or a related field (e.g., Google Cloud Professional Data Engineer).
Experience with advanced machine learning models (e.g., deep learning, NLP) is a plus.
Strong project management skills with the ability to prioritize tasks and manage multiple initiatives simultaneously.
Why Join Us?
Competitive salary and benefits package.
Opportunities for professional growth and development.
A collaborative and innovative work environment.
Access to cutting-edge technology and tools.
Flexible working options (remote and/or in-office).