Data Scientist

Data Engineer 

Mandatory Requirements  

• Experience in AWS Glue 

• Experience in Apache Parquet  
• Proficient in AWS S3 and data lake  
• Knowledge of Snowflake 
• Understanding of file-based ingestion best practices. 
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS  
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies  
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform  

• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations  
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data. 
• Define process improvement opportunities to optimize data collection, insights and displays. 
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible  
• Identify and interpret trends and patterns from complex data sets  

• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.  
• Key participant in regular Scrum ceremonies with the agile teams   
• Proficient at developing queries, writing reports and presenting findings  
• Mentor junior members and bring best industry practices  

QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)  
• Strong background in math, statistics, computer science, data science or related discipline 
• Advanced knowledge one of language: Java, Scala, Python, C#  
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake   

• Proficient with 
• Data mining/programming tools (e.g. SAS, SQL, R, Python) 
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum) 
• Data visualization (e.g. Tableau, Looker, MicroStrategy) 
• Comfortable learning about and deploying new technologies and tools.  

• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.  
• Good written and oral communication skills and ability to present results to non-technical audiences  
• Knowledge of business intelligence and analytical tools, technologies and techniques. 

Familiarity and experience in the following is a plus:  

• AWS certification 
• Spark Streaming  
• Kafka Streaming / Kafka Connect  
• ELK Stack  
• Cassandra / MongoDB  

• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools 

At Livello we building machine-learning-based demand forecasting tools as well as computer-vision-based multi-camera product recognition solutions that detects people and products to track the inserted/removed items on shelves based on the hand movement of users. We are building models to determine real-time inventory levels, user behaviour as well as predicting how much of each product needs to be reordered so that the right products are delivered to the right locations at the right time, to fulfil customer demand.

Responsibilities

• Lead the CV and DS Team
• Work in the area of Computer Vision and Machine Learning, with focus on product (primarily food) and people recognition (position, movement, age, gender, DSGVO compliant).
• Your work will include formulation and development of a Machine Learning models to solve the underlying problem.
• You help build our smart supply chain system, keep up to date with the latest algorithmic improvements in forecasting and predictive areas, challenge the status quo
• Statistical data modelling and machine learning research.
• Conceptualize, implement and evaluate algorithmic solutions for supply forecasting, inventory optimization, predicting sales, and automating business processes
• Conduct applied research to model complex dependencies, statistical inference and predictive modelling
• Technological conception, design and implementation of new features
• Quality assurance of the software through planning, creation and execution of tests
• Work with a cross-functional team to define, build, test, and deploy applications

Requirements:

• Master/PHD in Mathematics, Statistics, Engineering, Econometrics, Computer Science or any related fields.
• 3-4 years of experience with computer vision and data science.
• Relevant Data Science experience, deep technical background in applied data science (machine learning algorithms, statistical analysis, predictive modelling, forecasting, Bayesian methods, optimization techniques).
• Experience building production-quality and well-engineered Computer Vision and Data Science products.
• Experience in image processing, algorithms and neural networks.
• Knowledge of the tools, libraries and cloud services for Data Science. Ideally Google Cloud Platform
• Solid Python engineering skills and experience with Python, Tensorflow, Docker
• Cooperative and independent work, analytical mindset, and willingness to take responsibility
• Fluency in English, both written and spoken.

Job Responsibilities: 

• Identify valuable data sources and automate collection processes 
• Undertake preprocessing of structured and unstructured data. 
• Analyze large amounts of information to discover trends and patterns 
• Helping develop reports and analysis. 
• Present information using data visualization techniques. 

• Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems. 
• Evaluating changes and updates to source production systems. 
• Develop, implement, and maintain leading-edge analytic systems, taking complicated problems and building simple frameworks 
• Providing technical expertise in data storage structures, data mining, and data cleansing. 
• Propose solutions and strategies to business challenges 

Desired Skills and Experience: 

• At least 1 year of experience in Data Analysis 
• Complete understanding of Operations Research, Data Modelling, ML, and AI concepts. 

• Knowledge of Python is mandatory, familiarity with MySQL, SQL, Scala, Java or C++ is an asset 
• Experience using visualization tools (e.g. Jupyter Notebook) and data frameworks (e.g. Hadoop) 
• Analytical mind and business acumen 
• Strong math skills (e.g. statistics, algebra) 
• Problem-solving aptitude 

• Excellent communication and presentation skills. 
• Bachelor’s / Master's Degree in Computer Science, Engineering, Data Science or other quantitative or relevant field is preferred  

Roles and

Responsibilities

Seeking AWS Cloud Engineer /Data Warehouse Developer for our Data CoE team to

help us in configure and develop new AWS environments for our Enterprise Data Lake,

migrate the on-premise traditional workloads to cloud. Must have a sound

understanding of BI best practices, relational structures, dimensional data modelling,

structured query language (SQL) skills, data warehouse and reporting techniques.

 Extensive experience in providing AWS Cloud solutions to various business

use cases.

 Creating star schema data models, performing ETLs and validating results with

business representatives

 Supporting implemented BI solutions by: monitoring and tuning queries and

data loads, addressing user questions concerning data integrity, monitoring

performance and communicating functional and technical issues.

Job Description: -

This position is responsible for the successful delivery of business intelligence

information to the entire organization and is experienced in BI development and

implementations, data architecture and data warehousing.

Requisite Qualification

Essential

-

AWS Certified Database Specialty or -

AWS Certified Data Analytics

Preferred

Any other Data Engineer Certification

Requisite Experience

Essential 4 -7 yrs of experience

Preferred 2+ yrs of experience in ETL & data pipelines

Skills Required

Special Skills Required

 AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc.

 Bigdata: Databricks, Spark, Glue and Athena

 Expertise in Lake Formation, Python programming, Spark, Shell scripting

 Minimum Bachelor’s degree with 5+ years of experience in designing, building,

and maintaining AWS data components

 3+ years of experience in data component configuration, related roles and

access setup

 Expertise in Python programming

 Knowledge in all aspects of DevOps (source control, continuous integration,

deployments, etc.)

 Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD

 Hands on ETL development experience, preferably using or SSIS

 SQL Server experience required

 Strong analytical skills to solve and model complex business requirements

 Sound understanding of BI Best Practices/Methodologies, relational structures,

dimensional data modelling, structured query language (SQL) skills, data

warehouse and reporting techniques

Preferred Skills

Required

 Experience working in the SCRUM Environment.

 Experience in Administration (Windows/Unix/Network/Database/Hadoop) is a

plus.

 Experience in SQL Server, SSIS, SSAS, SSRS

 Comfortable with creating data models and visualization using Power BI

 Hands on experience in relational and multi-dimensional data modelling,

including multiple source systems from databases and flat files, and the use of

standard data modelling tools

 Ability to collaborate on a team with infrastructure, BI report development and

business analyst resources, and clearly communicate solutions to both

technical and non-technical team members