Senior Engineer Consultant-Data Science

Data Science:

• Knowledge of experimental design and testing frameworks like A/B testing, Multi-armed Bandittesting etc. to guide optimal decisions across various key base-management initiatives related tochurn reduction, revenue growth and customer satisfaction. Build frame-works to enable effective measurement of experiments at scale.
• Research and build proof-of-concept models utilizing various machine learning techniques andtraditional statistical techniques to drive optimal business decisions for various use cases like call-routing, revenue growth through initiatives.
• Build Financial models leveraging Survival modeling and other machine learning techniques to todrive effective decisions across all base-management initiatives.
• Develop Customer Segmentation Models and response rate models to help in effective targetingof customers across different base-management initiatives.
• KPI forecasting leveraging time-series forecasting techniques to guide the business on metricslike churn etc.
• Generate business insights by using various predictive modeling techniques.

Analytics and Data Enablement:

• Synthesizing predictive insights to concrete business actions and collaborate with stakeholders across the organization to drive successful business outcomes.
• Leveraging understanding of customer behaviors, strategic thinking, strong financial acumen and cross-functional aptitude to build analytical solutions to make the best informed decisions.
• Guiding the build and enhancement of the Solution specific features & insights with 360 degree view of customer profiles, interactions & demographics. Enabling team with Analytical solutions to evaluate marketing campaign's effectiveness and identify areas for optimization. Measure key performance indicators (KPIs) such as conversion rates, return on investment (ROI), and customer engagement metrics.
• Providing insights to refine targeting strategies, messaging, and channel allocation for future campaigns.

What we're looking for:

You'll need to have:

• Bachelor's degree or four or more years of work experience.
• Four or more years of relevant work experience.
• Strong Prescriptive & predictive data science experience.
• Advanced proficiency in SQL, Python (/R), GCP and data visualization tools (Tableau, Qlik or native Python or other libraries like Plotly/Streamlit etc).
• Proficiency with Microsoft Excel and PowerPoint.
• Experience managing large complex projects involving multiple work streams and stakeholders.
• Strong storytelling to drive recommendations based on the data analysis and articulate tradeoffs and communication plan to senior executives.
• Ability to translate complex ideas and express them in concise, simple to understand ways.
• Proven ability to take initiative, influence others and achieve results.
• Experience gathering, organizing and analyzing large amounts of information.
• Experience presenting ideas and content to a variety of stakeholders at various levels.
• Experience working collaboratively with a variety of stakeholders.
• Advanced research, analytical, and critical thinking skills with the ability to see things not readilyapparent to others and to find unique solutions to complex challenges.
• Ability to present and interact with all levels of management
• Ability to explain both the code and the underlying math used in algorithms/models.
• Experience in both batch and streaming models in production.
• Knowledge of math, probability, statistics, and AI/ML models.
• Experience in data structures, data modeling and software architecture skills.
• Good cross-functional collaboration skills.

Even better if you have one or mor of the following:

• Advanced degree in Computer Science, Mathematics or similar field.
• Experience working in analytical projects in telecom domain.
• Accuracy and attention to detail.
• Experience in data lake (hadoop), SQL, ETL.
• Problem solving, analytical, and research skills.
• Excellent verbal and written communication.
• Experience presenting to and influencing functional leaders and partners.
• Ability to work effectively independently and willingness to learn new technologies.
• Experience working with cross-functional teams in a dynamic environment.