We’re Hiring: Data Scientist / Machine Learning Engineer (5–7 years experience)

Are you passionate about turning data into real business impact? We’re looking for a Data Scientist / ML Engineer to join our team and help productionize cutting-edge predictive models that power smarter decisions in the fintech and customer engagement space.

What You’ll Do:

• Build, deploy, and optimize predictive models across lending, collections, and CRM use cases.
• Work hands-on with large-scale datasets and modern data pipelines.
• Collaborate with cross-functional teams to translate business challenges into data-driven solutions.
• Apply best practices in MLOps, model monitoring, and governance.
• Communicate insights effectively to drive strategy and roadmap decisions.

What We’re Looking For:

• 4–7 years’ experience as a Data Scientist or ML Engineer, with proven experience productionizing ML models.
• Expertise in Python and libraries like scikit-learn, pandas, numpy, xgboost, PyTorch/TensorFlow, spaCy/NLTK.
• Strong SQL skills and comfort with cloud data lakes, ETL pipelines, and large messy datasets.
• Experience deploying models via REST APIs, Docker, batch/streaming workflows.
• Familiarity with data visualization / BI tools for business reporting.
• A practical MLOps mindset—versioning, monitoring, retraining, and governance.
• Excellent communicator who can operate independently and thrive in dynamic environments.

Nice-to-Have Skills:

Experience with cloud ML platforms (SageMaker, Vertex AI, Azure ML, Databricks).

NLP/NLU for chat or voice bots.

Reinforcement learning or optimization exposure.

Experience in regulated industries with focus on explainable AI.

Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, Dataiku).

Contributions to open-source or research publications.

Interested candidates kindly share your resumes on [email protected]