Location
Secunderabad | India
Job description
Responsibilities - 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
- 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
- BE/BS in Computer Science, Math, Physics, or other technical fields.
Skills, Abilities, Knowledge:
- Data Science - Hands on experience and strong knowledge implementing productionizing machine learning models - supervised and unsupervised models. Deployment of models in am MLOps framework is required. Knowledge of Demand Forecast models is a plus.
- 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 is a plus
- Cloud (Azure) - Experience in Databricks and ADF is required
- 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
- Experience working with Retail/CPG Syndicated Data sources, including IRI, Nielsen is a plus
- Experience building solutions in the Commercial, Net revenue Management or Supply chain space is a plus
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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