Data Engineering Manager at Network Science · Mumbai, Navi Mumbai · 5 - 8 years · ₹20L - ₹25L / yr · Bootstrapped · Posted 15 Sep 2022
- Collaborate with the business teams to understand the data environment in the organization; develop and lead the Data Scientists team to test and scale new algorithms through pilots and subsequent scaling up of the solutions
- Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service
- Act as the single point source for all data related queries; strong understanding of internal and external data sources; provide inputs in deciding data-schemas
- Design, develop and maintain the framework for the analytics solutions pipeline
- Provide inputs to the organization’s initiatives on data quality and help implement frameworks and tools for the various related initiatives
- Work in cross-functional teams of software/machine learning engineers, data scientists, product managers, and others to build the AI ecosystem
- Collaborate with the external organizations including vendors, where required, in respect of all data-related queries as well as implementation initiatives

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Hiring for Data Scientist / Senior Data Scientist
Exp : 4 - 12 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Notice Period : Immediate - 15 days
Skills :
4+ years of experience in data engineering, data science, or related domains.
Hands-on experience with SQL, Python, and distributed data systems.
Knowledge of machine learning techniques and statistical analysis.
Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
Familiarity with DevOps practices and CI/CD for data pipelines.
Platforms & Operations Experience (Preferred)
- Experience working with Azure, AWS, or Google Cloud data tools.
Operational experience with data orchestration tools (Airflow, ADF, Glue).
Understanding of Kubernetes, Docker, or containerized environments.
Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).
Experience in monitoring, logging, and alerting operations for data workflows.
We are looking for a hands-on Lead Data Scientist with strong analytical, machine learning, and problem-solving skills to work in a client-facing environment.
The role requires someone who can independently identify opportunities, formulate hypotheses, design solutions, and drive initiatives from analysis through experimentation and production implementation. The candidate should also be comfortable guiding team members and working closely with engineering and client stakeholders.
Responsibilities:
- Analyse complex datasets to identify patterns, issues, and opportunities.
- Formulate and validate hypotheses through structured analysis and experimentation.
- Build and improve machine learning and anomaly detection solutions.
- Design end-to-end solutions considering data, modelling, engineering, and production constraints.
- Perform root cause analysis across models, data, and systems.
- Work with engineering teams on feature pipelines, model inference, and production deployment.
- Lead technical discussions with clients and communicate recommendations, trade-offs, and expected impact.
- Guide team members on analysis, modelling, and solution design.
- Proactively identify initiatives and roadmap items that can add value to the project.
Requirements:
- Strong foundation in statistics and machine learning.
- Strong hands-on experience with Python and SQL.
- Hands-on experience with Python ML and data frameworks such as Pandas, NumPy, scikit-learn, TensorFlow/Keras, Dask, Matplotlib, Boto3 SageMaker Python SDK, and Horovod.
- Strong data analysis, hypothesis-generation, and problem-solving skills.
- Experience with standard supervised and unsupervised ML techniques.
- Experience with anomaly detection techniques such as Isolation Forest and Autoencoders.
- Experience building and deploying production ML solutions.
- Working knowledge of data engineering and real-time / batch inference environments.
- Strong communication and stakeholder-management skills.
- Ability to lead technical work and guide cross-functional teams.
Good to Have:
- Experience in fraud detection or risk modelling.
- Experience with Graph Neural Networks.
- Exposure to real-time systems, streaming features, and low-latency data stores.
- Experience in AdTech, e-commerce, gaming, mobile applications, or similar high-volume consumer platforms.







