Collect, clean, and prepare structured and unstructured data from various sources.
Develop and implement machine learning models, statistical algorithms, and predictive analytics.
Perform exploratory data analysis (EDA) and extract meaningful insights to support decision-making.
Build data pipelines and automate model workflows in collaboration with data engineering teams.
Communicate insights clearly to stakeholders through dashboards, visualizations, and presentations.
Monitor model performance, perform retraining, and maintain model accuracy and stability.
Work closely with product, engineering, and business teams to identify opportunities for data-driven improvements.
Stay updated with the latest research, tools, and technologies in data science and AI.
Required Skills & QualificationsBachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science or related fields.
Strong proficiency in Python or R, with experience in data libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
Expertise in machine learning algorithms, model evaluation, and optimization.
Experience with SQL and working with large datasets.
Knowledge of data visualization tools such as Tableau, Power BI, or matplotlib/seaborn.
Strong understanding of statistical concepts and their application in business scenarios.
Ability to translate complex data into clear, actionable insights.
Preferred QualificationsExperience with big data technologies (Spark, Hadoop, Databricks).
Exposure to cloud platforms (AWS, Azure, GCP).
Knowledge of NLP, deep learning, or advanced ML techniques.
Experience in domain-specific analytics (BFSI, retail, healthcare, etc.).
Familiarity with MLOps and deploying models in production environments.
CompetenciesStrong analytical and problem-solving skills.
Excellent communication and storytelling ability.
Detail-oriented with a focus on data accuracy.
Ability to work independently and collaboratively in a cross-functional team.
ResponsibilitiesDevelop machine learning models to solve complex business problems
QualificationsGraduate 4 - 6 years
Skills Required
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or related field.
- 4 - 6 years of professional experience (graduate-level experience indicated).
- Strong proficiency in Python or R with experience in Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
- Expertise in machine learning algorithms, model evaluation, and optimization.
- Experience with SQL and working with large datasets.
- Knowledge of data visualization tools such as Tableau, Power BI, matplotlib, or seaborn.
- Strong understanding of statistical concepts and their application to business scenarios.
- Ability to translate complex data into clear, actionable insights and communicate to stakeholders.
- Build data pipelines and automate model workflows in collaboration with data engineering teams.
- Experience with big data technologies (Spark, Hadoop, Databricks).
- Exposure to cloud platforms (AWS, Azure, GCP).
- Knowledge of NLP, deep learning, or other advanced ML techniques.
- Familiarity with MLOps and deploying models in production environments.
- Experience in domain-specific analytics (BFSI, retail, healthcare, etc.).
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
