Key Responsibilities


● Lead and execute end -to -end data science
projects, encompassing problem definition, data exploration, model creation,
assessment, and deployment.

● Develop
and deploy predictive models, optimization techniques, and statistical analyses
to address tangible business needs.

● Articulate
complex findings through clear and persuasive storytelling for both technical
experts and non -technical stakeholders.

● Spearhead
experimentation methodologies, such as A/B testing, to enhance product features
and overall business outcomes.

● Partner
with data engineering teams to establish dependable and scalable data
infrastructure and production -ready models.

● Guide and mentor junior data scientists,




while also fostering team best practices and contributing to research endeavours.

Required
Qualifications & Skills:

● Bachelor’s
or master’s degree in computer science, Engineering, or a related field

● 8+
years of practical experience in data science, including deploying models to
production.

● Expertise
in Python and SQL;

● Solid
background in ML frameworks such as scikit -learn, TensorFlow, PyTorch, and
XGBoost.

● Competence
in data visualization tools like Tableau, Power BI, matplotlib, and Plotly.

● Comprehensive
knowledge of statistics, machine learning principles, and experimental design.

● Experience
with cloud platforms (AWS, GCP, or Azure) and Git for version control.

● Exposure
to MLOps tools and methodologies (e.g., MLflow, Kubeflow, Docker, CI/CD).

● Familiarity
with NLP, time series forecasting, or recommendation systems is a plus.

● Knowledge
of big data technologies (Spark, Hive, Presto) is desirable.