Data Scientist

Data Scientist

ONSITE - Miami, FL 33102

6+ Months Contract

Qualifications & Skills:
- **Education:** Masters of PhD degree in Data Science, Computer Science, Statistics, or a related field.
- **Experience:**
- 3+ years in data science, preferably in customer service, utilities, or a related industry.
- Proficiency in Python/R, SQL, and data visualization tools (Tableau, Power BI).
- Experience with machine learning (scikit-learn, TensorFlow, PyTorch) and NLP.
- Familiarity with cloud platforms (preferable AWS) and big data tools (Spark, Hadoop) is a plus.
- **Soft Skills:**
- Strong problem-solving and analytical thinking.
- Ability to translate technical findings into business recommendations.
- Excellent communication and teamwork skills.

We are seeking a skilled data scientist to join our customer service team. In this role, you will leverage data analytics, machine learning, and statistical modeling to enhance customer service operations, improve customer satisfaction, and optimize service delivery. You will work closely with cross-functional teams to extract insights from customer interactions, predict service trends, and develop data-driven solutions that drive efficiency and customer engagement. Key Responsibilities: 1. **Data Analysis & Insights:**
- Analyze large datasets from customer service interactions (call logs, chat transcripts, surveys, billing data, etc.) to identify trends and pain points.

2. **Predictive & Prescriptive Modeling:**
- Build machine learning models to predict customer next best action, service outages, and high-risk accounts.
- Develop recommendation systems to personalize customer interactions and improve issue resolution. 3. **Process Optimization:**
- Use AI and automation to improve customer service workflows (e.g., chatbots, routing optimization).
- Collaborate with IT and operations teams to integrate data-driven solutions into customer service platforms. 4. **Customer Segmentation & Personalization:**
- Apply clustering techniques to segment customers based on behavior, preferences, and service needs.
- Design targeted retention and engagement strategies using data insights. 5. **Natural Language Processing (NLP):**
- Analyze customer feedback (emails, surveys, call transcripts) using sentiment analysis and topic modeling to improve service quality.
- Enhance chatbot and virtual assistant capabilities using NLP techniques. 6. **Stakeholder Collaboration:**
- Present findings to leadership and business teams in a clear, actionable manner.
- Work with customer service managers to implement data-backed improvements.