Job Description
The Team:
You will be work closely in a cross functional world class AI ML team comprised of experts in
Backend/Frontend engineering, Data Modeling, ML & LLMOps.
Responsibilities and Impact:
Method Application:
o Proficient to decode, integrate various statistical and analytical methods, techniques
and functions ensuring high statistical rigor and accuracy of model results and
outcomes.
o Build a process to compare model results with internal or external benchmarks for
testing and reliability
o High level of experience in ML DevOps for both supervised or unsupervised learning
methods
o Retail, CPG, Manufacturing verticals experience desirable
o Experience in Method application in Uni-variate Forecasting, Causal forecasting, Price
Elasticity modelling, Customer Churn, Anomaly Detection, Market Matching, Marketing
Mix Modeling, Customer Segmentation, Store Clustering
Solution Engineering
o Strong programming skills in languages such as Python, Java, or Scala
o Experience with containerization technologies such as Docker and Kubernetes
Data ETL
o Experience working with Scintilla, Nielsen, Circana, Retail Media Network data
o Data ETL automation with ability to manage large volumes of data and build agentic
data enrichment pipelines. Expertise in data pipeline tools such as Apache Spark,
Apache Beam, or Apache Flink
o Experience with data warehousing and data lake technologies such as Oracle Object
Storage, Apache Hadoop, Apache Hive, or Amazon Redshift or Azure Synapse,
Postgres SQL
o Ability to work with embedded BI solutions
o Solid understanding of different data structures and algorithms to design and
implement efficient and scalable data processing systems
o Strong understanding of data governance, data quality, and data security principles
Insights Generation
o Strong focus on data to action to generate and deliver insights, and telling stories with
data
Workflow Improvements and Monitoring
o Performance Monitoring: Monitor the performance of Data Science workflows,
troubleshoot issues, and optimize algorithms for efficiency and accuracy. Familiar with
development best practices (unit testing, code versioning, reproducibility)
o Documentation: Develop and maintain comprehensive documentation on AI & Data
Science models, algorithms, and deployment processes., knowledge base, including
development best practices, MLOPs processes and procedures.
o Collaboration and Training: Collaborate with cross-functional teams to integrate
machine learning models into production systems. Work closely with members of
technology teams in the development, and implementation of Naukr AI platform.
What We’re Looking For:
o 4 year under-graduate degree in Computer Science, Engineering, or a related field from a Tier
1/2 university. Only accredited universities with regional or national entrance examinations.
o 4+ years of hands-on experience in data science domain
o Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-lear or
Pandas, Numpy et alia.
o Experience with cloud-based data platforms such as AWS, GCP, or Azure
o Experience with data visualization tools such as Oracle Analytics Cloud, Tableau, Power BI, or
D3.js
o Experience with SageMaker and/or Vertex AI or Azure AI Foundry or Databricks
o Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, MLflow.
o Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools.
o Experience with agile development methodologies and version control systems such as Git or
Bitbucket
o Show Progressive experience as in machine learning, data engineering or similar roles.
o Experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions
