- Design, develop, and deploy machine learning algorithms and models to solve complex problems.
- Use predictive modeling to increase and optimize customer experiences, revenue generation and other business outcomes.
- Collaborate with cross-functional teams to understand business needs and deliver effective data-driven solutions.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
Education : Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a related field.
Minimum qualification: 9+ years of IT experience, with at least 4 years focused on data science related solution delivery.
Required Competencies:
- Proficiency in programming (Python, R, or Java, SQL, NoSQL) to draw insights from large data sets.
- Experience with machine learning frameworks (eg, TensorFlow, PyTorch) and libraries (eg, scikit-learn, pandas).
- Experience with NLP & transformer-based models (eg, BERT, GPT, Llama).
- Proficiency in statistical methods, hypothesis testing, confidence intervals, and p-values.
- Knowledge of time series modeling, trend analysis, and forecasting using methods like ARIMA and Prophet.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc) and their real-world advantages/drawbacks.
- Having an exposure to LLM and Gen AI concepts, exposure to DevOps CI/CD pipelines is a plus
- Solid foundation in data structures, algorithms, and software engineering principles.
- Excellent problem-solving, analytical, and communication skills.
Preferred Experience:
- Experience with cloud computing platforms (eg, AWS, Azure, GCP).
- Familiarity with big data technologies (eg, Hadoop, Spark).
- Experience visualizing/presenting data for stakeholders using tools like Tableau/Power BI/Matplotlib/Seaborn etc
