EXL is looking for a Data Scientist who will play a crucial role in providing analytics and data science support to a client within our Sports, Media and Entertainment practice. The primary responsibility of this role is to leverage your expertise in analytics, data science, machine learning and AI to empower the client in making informed business decisions. You will work with a dynamic team and will have true ownership and impact over developing analytics solutions and data products for the stakeholders.
Responsibilities for Internal Candidates
- Collaborate with the client in the sport sector to understand their business objectives and challenges and ensure the delivery of high-quality analytics/data science solutions.
- Design and build end to end machine learning solutions and statistical frameworks across fan behavior.
- Own the full modeling lifecycle: problem framing, feature engineering, model selection, cross validation and hyperparameter tuning
- Lead recurring analytical programs with a focus on reproducibility and automation.
- Partner with data engineering to integrate model outputs into operational systems and stakeholder facing products.
- Utilize your strong analytical and problem-solving skills to extract meaningful insights from data and contribute to data-driven decision-making.
- Use variety of analytical tools (SQL, Python) and techniques (regression, decision trees, machine learning concepts etc.) to carry out analyses, create ML models and drive conclusions.
- Support the integration of data science capabilities for the client to help solve tangible problems with measurable impact.
- Contribute to the continuous improvement of analytics processes and methodologies.
Core Skills (Required):
- Bachelor’s degree in economics, mathematics, computer science/engineering, operations research or related analytics areas
- 2+ years of hands-on experience in a data science role with a track record of shipping models into production.
- Extremely proficient in SQL for robust data extraction and analysis.
- Strong programming skills in Python.
- Familiarity with Git and code/data version control.
- Solid statistical foundation
- Exposure to NLP techniques for processing unstructured survey data.
- Excellent communication, problem-solving, and critical thinking skills.
- Self-started and willingness to take on challenging initiatives
- Effective time management and attention to detail
- Familiarity with MLOps concepts
