Data Science / ML engineer - Manager
Data Science / ML engineer - Manager
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Job Description
We are seeking a highly skilled Data Scientist / ML Engineer with a strong foundation in data engineering (ELT data pipelines) and advanced machine learning to develop and deploy sophisticated models. The role focuses on building scalable data pipelines developing ML models and deploying solutions in production to support a cuttingedge reporting insights and recommendations platform for measuring and optimizing online marketing campaigns.
The ideal candidate should be comfortable working across data engineering ML model lifecycle and cloudnative technologies.
Job Description:
Key Responsibilities:
1. Data Engineering & Pipeline Development
- Design build and maintain scalable ELT pipelines for ingesting transforming and processing largescale marketing campaign data.
- Ensure high data quality integrity and governance using orchestration tools like Apache Airflow Google Cloud Composer or Prefect.
- Optimize data storage retrieval and processing using BigQuery Dataflow and Spark for both batch and realtime workloads.
- Implement data modeling and feature engineering for ML use cases.
2. Machine Learning Model Development & Validation
- Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization.
- Experiment with different algorithms (regression classification clustering reinforcement learning) to drive insights and recommendations.
- Leverage NLP timeseries forecasting and causal inference models to improve campaign attribution and performance analysis.
- Optimize models for scalability efficiency and interpretability.
3. MLOps & Model Deployment
- Deploy and monitor ML models in production using tools such as Vertex AI MLflow Kubeflow or TensorFlow Serving.
- Implement CI/CD pipelines for ML models ensuring seamless updates and retraining.
- Develop realtime inference solutions and integrate ML models into BI dashboards and reporting platforms.
4. Cloud & Infrastructure Optimization
- Design cloudnative data processing solutions on Google Cloud Platform (GCP) leveraging services such as BigQuery Cloud Storage Cloud Functions Pub/Sub and Dataflow.
- Work on containerized deployment (Docker Kubernetes) for scalable model inference.
- Implement costefficient serverless data solutions where applicable.
5. Business Impact & Crossfunctional Collaboration
- Work closely with data analysts marketing teams and software engineers to align ML and data solutions with business objectives.
- Translate complex model insights into actionable business recommendations.
- Present findings and performance metrics to both technical and nontechnical stakeholders.
Qualifications & Skills:
Educational Qualifications:
Bachelors or Masters degree in Computer Science Data Science Machine Learning Artificial Intelligence Statistics or a related field.
Certifications in Google Cloud (Professional Data Engineer ML Engineer) is a plus.
MustHave Skills:
Experience: 510 years with the mentioned skillset & relevant handson experience
Data Engineering: Experience with ETL/ELT pipelines data ingestion transformation and orchestration (Airflow Dataflow Composer).
ML Model Development: Strong grasp of statistical modeling supervised/unsupervised learning timeseries forecasting and NLP.
Programming: Proficiency in Python (Pandas NumPy Scikitlearn TensorFlow/PyTorch) and SQL for largescale data processing.
Cloud & Infrastructure: Expertise in GCP (BigQuery Vertex AI Dataflow Pub/Sub Cloud Storage) or equivalent cloud platforms.
MLOps & Deployment: Handson experience with CI/CD pipelines model monitoring and version control (MLflow Kubeflow Vertex AI or similar tools).
Data Warehousing & Realtime Processing: Strong knowledge of modern data platforms for batch and streaming data processing.
NicetoHave Skills:
Experience with Graph ML reinforcement learning or causal inference modeling.
Working knowledge of BI tools (Looker Tableau Power BI) for integrating ML insights into dashboards.
Familiarity with marketing analytics attribution modeling and A/B testing methodologies.
Experience with distributed computing frameworks (Spark Dask Ray).
Location:
BengaluruBrand:
MerkleTime Type:
Full timeContract Type:
PermanentRequired Experience:
Manager
Employment Type
Full-Time
