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Job Location: Gurugram
Job Detail:
- Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
- Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities
- Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards
- Use big data technologies to help process data and build scaled data pipelines (batch to real time)
- Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines leveraging the NGAA platform (Azure)
- Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure
- Automate ML models deployments
Qualifications:
- 4 – 7 years of overall experience that includes at least 4 + years of hands-on work experience data science / Machine learning
- Minimum 4 + year of SQL experience
- Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers (Azure preferred) is preferred
- B E /BS in Computer Science, Math, Physics, or other technical fields.
Skills, Abilities, Knowledge:
- Data Science – Hands on experience and strong knowledge of building machine learning models – supervised and unsupervised models
- Programming Skills – Hands-on experience in statistical programming languages like Python , R and database query languages like SQL
- Statistics – Good applied statistical skills, including knowledge of statistical tests , distributions, regression, maximum likelihood estimators
- Cloud ( Azure ) – Experience in Databricks and ADF is desirable
- Familiarity with Spark, Hive, Pig is an added advantage
- Model deployment experience will be a plus
- Experience with version control systems like GitHub and CI/CD tools
- Experience is Exploratory data Analysis
- Knowledge of ML Ops / DevOps and deploying ML models is required
- Experience using MLFlow, Kubeflow etc. will be preferred
- Experience executing and contributing to ML OPS automation infrastructure is good to have
- Exceptional analytical and problem-solving skills
Differentiating Competencies Required
- Ability to work with virtual teams (remote work locations); lead team of technical resources (employees and contractors) based in multiple locations across geographies
- Lead technical discussions, driving clarity of complex issues/requirements to build robust solutions
- Strong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirements
- Able to work independently with business partners to understand requirements quickly, perform analysis and lead the design review sessions
- Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business
- Places the user in the centre of decision making
- Teams up and collaborates for speed, agility, and innovation
- Experience with and embraces agile methodologies
- Strong negotiation and decision-making skill
- Experience managing and working with globally distributed teams
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