Data Scientist

We are looking for

A Natural Language Processing (NLP) expert with strong computer science fundamentals and experience in working with deep learning frameworks. You will be working at the cutting edge of NLP and Machine Learning.

Roles and Responsibilities

Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.

Mentor and coach other team members

Evaluate the performance of NLP models and ideate on how they can be improved

Support internal and external NLP-facing APIs

Keep up to date on current research around NLP, Machine Learning and Deep Learning

Mandatory Requirements

Any graduation with at least 2 years of demonstrated experience as a Data Scientist.

Behavioral Skills

Strong analytical and problem-solving capabilities.

Proven ability to multi-task and deliver results within tight time frames

Must have strong verbal and written communication skills

Strong listening skills and eagerness to learn

Strong attention to detail and the ability to work efficiently in a team as well as individually

Hands-on experience with

NLP

Deep Learning

Machine Learning

Python

Bert

Job Description – Data Science  

Basic Qualification:

• ME/MS from premier institute with a background in Mechanical/Industrial/Chemical/Materials engineering.
• Strong Analytical skills and application of Statistical techniques to problem solving
• Expertise in algorithms, data structures and performance optimization techniques
• Proven track record of demonstrating end to end ownership involving taking an idea from incubator to market
•   Minimum years of experience in data analysis (2+), statistical analysis, data mining, algorithms for optimization.

Responsibilities

The Data Engineer/Analyst will

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  
• Clear interaction with Business teams including product planning, sales, marketing, finance for defining the projects, objectives.
  
• Mine and analyze data from company databases to drive optimization and improvement of product and process development, marketing techniques and business strategies
  
• Coordinate with different R&D and Business teams to implement models and monitor outcomes.
  
• Mentor team members towards developing quick solutions for business impact.
  
• Skilled at all stages of the analysis process including defining key business questions, recommending measures, data sources, methodology and study design, dataset creation, analysis execution, interpretation and presentation and publication of results.
  

• 4+ years’ experience in MNC environment with projects involving ML, DL and/or DS
  
• Experience in Machine Learning, Data Mining or Machine Intelligence (Artificial Intelligence)
  
• Knowledge on Microsoft Azure will be desired.
  
• Expertise in machine learning such as Classification, Data/Text Mining, NLP, Image Processing, Decision Trees, Random Forest, Neural Networks, Deep Learning Algorithms
  
• Proficient in Python and its various libraries such as Numpy, MatPlotLib, Pandas
  
• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to Business Teams.
  
• Experience in infra development / building platforms is highly desired.
  
• A drive to learn and master new technologies and techniques.
  

Work with the manager through the entire analytical and machine learning model life cycle:

⮚ Define the problem statement

⮚ Build and clean datasets

⮚ Exploratory data analysis

⮚ Feature engineering

⮚ Apply ML algorithms and assess the performance

⮚ Codify for deployment

⮚ Test and troubleshoot the code

⮚ Communicate analysis to stakeholders

Technical Skills

⮚ Proven experience in usage of Python and SQL

⮚ Excellent in programming and statistics

⮚ Working knowledge of tools and utilities - AWS, DevOps with Git, Selenium, Postman, Airflow, PySpark

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.

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.