The ideal candidate should have hands-on experience across the complete data science lifecycle, including data exploration, feature engineering, model development, evaluation, deployment, monitoring, and optimization.
Responsibilities
- Analyze large structured and unstructured datasets to identify patterns, trends, and actionable insights.
- Develop and implement machine learning and statistical models for business use cases.
- Perform data cleaning, preprocessing, exploratory data analysis, and feature engineering.
- Build predictive models using supervised and unsupervised learning techniques.
- Develop solutions for classification, regression, clustering, forecasting, anomaly detection, and recommendation use cases.
- Use Python and SQL for data manipulation, analysis, and model development.
- Develop and optimize ML models using libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
- Design appropriate model validation and evaluation strategies using relevant performance metrics.
- Build reusable data science pipelines and production-ready ML solutions.
- Collaborate with Data Engineers, ML Engineers, Software Engineers, Product Owners, and business stakeholders.
- Work with large-scale data processing platforms and cloud environments.
- Deploy machine learning models through APIs, batch processing, or real-time inference pipelines.
- Implement MLOps practices covering model versioning, deployment, monitoring, retraining, and governance.
- Develop prototypes and proof-of-concepts for new AI/ML use cases.
- Present complex analytical findings to both technical and non-technical stakeholders.
- Ensure data quality, security, privacy, explainability, and responsible AI practices.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, Engineering, or a related discipline.
- 5+ years of relevant experience in Data Science, Machine Learning, or advanced analytics.
- Strong analytical and problem-solving capabilities.
- Excellent communication and stakeholder-management skills.
- Ability to translate business problems into appropriate data science and AI/ML solutions.
- Experience working in Agile and enterprise development environments.
- Banking, payments, financial services, or other large-scale enterprise experience is preferred.
At Zensar, we’re
“experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose:
Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is
ONE with Client - a set of four core values that reflect who we are and how we work:
One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore
Life at Zensar and join us to
Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
— Sarah J.
·
Marketing Manager
★★★★★
Verified
