Data Scientist
3 weeks ago
Data Scientist
Join a collaborative interdisciplinary team focused on data where you will be responsible for delivering statistical/ML models continuously. You will work closely with process owners, product owners, and business stakeholders to gain a deep understanding of project requirements.
Responsibilities
- Project Delivery : Deliver Advanced Analytics/Data Science projects within time constraints while ensuring adherence to enterprise architecture standards.
- Code Development : Contribute actively to code and development in projects and services.
- Data Access : Collaborate with data engineers to ensure seamless data access for discovery and prepare data for model consumption.
- Industrialization : Partner with ML engineers working on industrializing models.
- Service Design : Communicate with business stakeholders during service design, training, and knowledge transfer.
- Experimentation : Support large-scale experimentation and build data-driven models.
- Requirement Refinement : Refine project requirements into modeling problems.
- Influencing Product Teams : Influence product teams through data-based recommendations.
- Methodology Research : Stay up-to-date with state-of-the-art methodologies.
- Documentation : Create documentation for learnings and knowledge transfer.
- Packages/Libraries : Develop reusable packages or libraries.
- Delivery Adherence : Ensure timely and budget-friendly delivery that meets project requirements.
- Data Processing : Leverage big data technologies to process data and build scaled data pipelines (batch to real-time).
- ML Lifecycle Implementation : Implement end-to-end ML lifecycle using Azure Machine Learning and Azure Pipelines.
- Model Deployment Automation : Automate ML models deployments.
Qualifications
- Education : BE/B.Tech in Computer Science, Maths, or related technical fields.
- Experience : 5+ years of experience as a Data Scientist.
- Commercial/Supply Chain Experience : 4+ years of experience building solutions in the commercial or supply chain space.
- Team Collaboration : 4+ years of experience working in a team to deliver production-level analytic solutions.
- Version Control/Git : Proficiency in git version control.
- Database Querying : Fluency in SQL syntax.
- Statistical Techniques : 4+ years of experience in Statistical/ML techniques for supervised (regression, classification) and unsupervised problems.
- Programming Skills : 4+ years of experience developing business problem-related statistical/ML modeling with industry tools, focusing on Python or Pyspark development.
Skill Set
- Data Science : Hands-on experience with machine learning models – supervised and unsupervised models. Knowledge of Time series/Demand Forecast models is an added advantage.
- Programming Skills : Hands-on experience in statistical programming languages like Python, Pyspark, and database query languages like SQL.
- Statistics : Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators.
- Cloud Computing : Experience in Databricks and ADF is desirable.
- Data Engineering Tools : Familiarity with Spark, Hive, Pig is an added advantage.
- Business Storytelling : Ability to communicate data insights in business consumable format. Proficiency in one Visualization tool.
- Soft Skills : Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities.
- Agile Methodology : Experience with Agile methodology for team work and analytics 'product' creation.
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