Lead Assistant Manager/Manager/Senior Manager - Data Scientist - Gen AI/LLM

Required Qualifications:

- Bachelors/master's in computer science or related field or equivalent work experience.

- 3+ years of Hands-on experience in in Data Science and ML models.

- Should have a good understanding of deep learning and large-scale ML concepts.

- Experience in data extraction and data manipulation in Python/R.

- Understanding of SAS/R modules is advantage

- Good knowledge of analytics, business insights generation, Data visualization tools like Power BI, Tableau

- Familiarity with cloud platforms such as Microsoft Azure or Amazon Web Services (AWS) for data storage, processing, and deployment of machine learning models.

- Strong and in-depth understanding of statistical concepts.

- Experience working in a research environment.

- Strong technical skills involving problem-solving, design and coding.

- Industry experience working on machine learning or systems software.

- Knowledge of agile or iterative Software Development Life Cycle.

- Independent and self-motivated.

- Cross team and cross org collaboration.

Role Overview:

As a Data Scientist at EXL, you will play a crucial role in driving insights and strategic decision-making for one of the UK's largest energy supplier. Your primary responsibility will be to develop and enhance demand forecasting models to optimize resource allocation, improve operational efficiency, and enhance customer experience.

Key Responsibilities:

- Demand Forecasting Modeling: Develop and maintain advanced statistical models to forecast energy demand accurately. Leverage machine learning algorithms and predictive analytics techniques to improve forecast accuracy.

- Data Analysis and Insights: Analyze large datasets to identify trends, patterns, and anomalies that impact energy demand. Generate actionable insights to support strategic planning and operational decisions.

- Model Evaluation and Improvement: Continuously evaluate the performance of demand forecasting models. Identify opportunities for model enhancement and optimization to align with business objectives.

- Collaboration and Stakeholder Management: Work closely with cross-functional teams, including business analysts, engineers, and stakeholders, to understand business requirements and translate them into analytical solutions.

- Documentation and Reporting: Document model development processes, methodologies, and results. Prepare clear and concise reports and presentations to communicate findings and recommendations to stakeholders.