Science, DataEng & ML Engineer Ssr (3 new open positions)

Senior Data Scientist - POC / SWAT

Responsibilities:
Process both structured and unstructured data, and analyze data to discover trends and patterns by exploring the data.
Build predictive models and machine learning algorithms and evaluate different models.
Build analytical solutions in the form of AI/ML product prototypes to solve customer problems.
Present insights using data visualization techniques.
Collaborate with engineering and product development teams to productionize the developed AI model.

Requirements:
Bachelors degree or higher in a relevant analytical field with at least 2 years of relevant domain experience in retail and CPG.
Skilled with data science programming in Python (pandas, writing classes, productionize the models) and SQL.
Experience in Statistical Modeling and Machine Learning.
Prototyping.
QA and testing.
Data Interpretation and Visualization.
Presentation skills.
Storytelling with data.

Skills
Python, Cloud engineering, SQL, Basic ML algorithms, Experience with Transaction data and time series data. Simple UI s.
Ability to understand large scale software & system architecture
Able to communicate technical issues with technical & non-technical stakeholders
Preferred Skills/Experience Nice to Have:
Experience with Python ML tools: Pytorch, Tensorflow, Jupyter Notebooks, Pandas, scikit-learn, Numpy
Experience with Spark
Experience with UI: Flask, Plotly, Streamlit
Understanding of Continuous integration, testing, deployment & release methodologies
Experience in Kaggle participation

Senior ML Engineer - Optimization Specialist

Responsibilities:
Execute and manage (hands-on) the whole machine learning lifecycle
Create automated ETL pipelines for training datasets
Create a ML pipeline to train, evaluate and deploy models
Collaborate with engineering and product development teams to productionize the developed AI model

Required Skills/Experience
Versatile in Python, Cloud engineering, SQL, Basic ML algorithms.
Multi objective optimization
Strong Statistical background
Comfortable with cloud-based platforms such as Azure Data Factory and Azure ML Pipeline
Have used version control applications like Gitlab

Preferred Skills/Experience Nice to Have:
Python ML frameworks: Pytorch, Jupyter Notebooks, Pandas, scikit-learn, Numpy
Have used PySpark or Azure Databricks Notebooks
Understand Continuous integration, testing, deployment & release methodologies

Data Engineer

Responsibilities:
Defining, building, and integrating data processing pipelines
Collaboratively working with other teams and the architect to design and develop solutions aligning with the architectural vision
Taking ownership of tasks/components and ensuring timely and quality delivery
Mentoring of fellow team members

Core Skills:
Extensive experience with large scale data processing pipelines and enabling technologies; e.g. Azure Data Factory, Databricks, Spark
Real world experience of operationally active data ingestion and automation
Extensive experience of programming languages: Python, SQL
Extensive experience with at least one major cloud platform, ideally Azure
Working knowledge of software development and associated technologies
Broad knowledge of software development and associated technologies
Proven problem solving ability and the ability to work independently as well as with a team
Strong communication skills and highly effective when working with a team

Highly Desirable Skills:
Experience of container technologies, especially Docker, and container orchestration technologies such as Kubernetes
Experience with Machine Learning training and serving pipelines