Job Title - Analyst - Data Science
The Data Science Lead will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Machine Learning Services and Pipelines.
You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments.
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
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, SPINS, and Numerator, for CPG commercial analytics use cases is a plus
Experience building solutions in the Commercial, Net revenue Management or Supply chain space is a plus
Differentiating Competencies Required
Maternity leave coaching
Backup child care
Onsite child care
Child care subsidies
Unconscious bias training
Remote work policy
Short term disability
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