Data Scientist

Key Skills
o Convert machine learning models into APIs for applications accessibility
o Running machine learning tests and experiments
o Implementing appropriate ML algorithms
o Creating machine learning models and retraining systems
o Study and transform data science prototypes
o Design machine learning systems
o Research and implement appropriate ML algorithms and tools
o Train and retrain systems when necessary
o Test and deploy models
o Use AI to empower the company with novel capabilities
o Designing and developing machine learning and deep learning system
o Outstanding analytical and problem-solving skills
• Alexa
o Excellent in Python programming
o Experience with AWS Lamda
o Experience with Alexa skills
o Alexa skill directives
• Google
o Excellent in NodeJS programming
o Experience with GCP - Dialog Flow and Actions on Google
o Using built-in intents and developing custom intents
o API integration and Postman knowledge

Qualifications

• 5+ years of professional experience in experiment design and applied machine learning predicting outcomes in large-scale, complex datasets.
• Proficiency in Python, Azure ML, or other statistics/ML tools.
• Proficiency in Deep Neural Network, Python based frameworks.
• Proficiency in Azure DataBricks, Hive, Spark.
• Proficiency in deploying models into production (Azure stack).
• Moderate coding skills. SQL or similar required. C# or other languages strongly preferred.
• Outstanding communication and collaboration skills. You can learn from and teach others.
• Strong drive for results. You have a proven record of shepherding experiments to create successful shipping products/services.
• Experience with prediction in adversarial (energy) environments highly desirable.
• Understanding of the model development ecosystem across platforms, including development, distribution, and best practices, highly desirable.

As a dedicated Data Scientist on our Research team, you will apply data science and your machine learning expertise to enhance our intelligent systems to predict and provide proactive advice. You’ll work with the team to identify and build features, create experiments, vet ML models, and ship successful models that provide value additions for hundreds of EE customers.

At EE, you’ll have access to vast amounts of energy-related data from our sources. Our data pipelines are curated and supported by engineering teams (so you won't have to do much data engineering - you get to do the fun stuff.) We also offer many company-sponsored classes and conferences that focus on data science and ML. There’s great growth opportunity for data science at EE.

Energy Exemplar is the market leader in Energy Modelling & Simulation Products. Energy Exemplar customers across the globe are modelling their energy markets with confidence to make billion-dollar decisions 

 

Job Overview for GIS Data Analyst 

 

You should be a self-starter with high motivation and will be a core member of the Energy Data team. You will be responsible for developing the company’s competence in geographic energy data collection, maintenance, and delivery to customers through our extensive suite of SaaS products.  Our products support companies engaged in power and natural gas markets on 6 continents.  Our customers are industry leaders in supply, transportation, delivery, operations and trading and our products allow our customers to deliver their optimal solution.  Our data are sourced from hundreds of websites in many languages and your job is to ensure that we have the geographic reference to make sense of the data. You will use your creativity, pattern recognition skills, satellite and aerial imagery and other public sources to provide geographic reference data across the energy industry.  You will work with the Energy Data Analysts to teach them basic GIS research capabilities.  Learnings out of this role will build foundation of skills necessary to advance to roles such as Energy Market Analyst or Data Scientist. 

  

Education & Experience 

 

• Master’s/Post Graduate Diploma degree in Geoinformatics/GIS, Geoinformatics & Natural Resources Engineering, Remote sensing & GIS, GIS/Spatial Data Science with Bachelors/Masters in Energy/Energy Management /Electrical Engg/Power System/Oil and Gas Management/Petroleum/Geophysics & Other Energy Industry related degrees would be preferred OR 

Master’s/Post Graduate Diploma degree/Bachelor’s in Geoinformatics/GIS, Geoinformatics & Natural Resources Engineering, Remote sensing & GIS, GIS/Spatial Data Science, or any engineering streams 

• 2+ years of experience working with GIS Systems/Database, GIS data management / GIS data handling and processing/GIS data engineering 

 

Essential/Necessary Skills 

  

• Proficiency in handling GIS data with SQL, Python/R 

• Exposure to mapping tools QGIS/ARCGIS/Visio/FME 
• Expertise in spatial modelling and geospatial analytics (Raster/Vector tools) 
• Proven experience working with geospatial data integration and testing  
• Outstanding communication and collaboration skills. 
• Strong drive for results. You have a proven record of shepherding experiments to create successful shipping products/services. 

 

About Energy Exemplar

Energy Exemplar is the global market leader in the technology of optimization-based energy market simulation. Our software suite, headlined by PLEXOS and Aurora, is used across every region of the world for a wide range of applications, from short-term analysis to long-term planning studies. Driven by the frenetic pace of advancements in computing technology and mathematical algorithms, our people continually think of novel approaches and more realistic simulations that enhance decision making, create market opportunities that benefit us all and enable utilities and regulatory authorities to become smarter, more energy efficient and profitable. Energy Exemplar continues to ‘push the envelope’, being first-to-market with the latest advances in mathematical programming and energy market simulation theory, as it strives to offer the most comprehensive simulation software to its customer base. Development continues to be headquartered in Adelaide, South Australia, led by Glenn Drayton and backed by a team with expertise in software development, operations research, economics, mathematics, statistics, and electrical engineering.

For more details, please visit http://www.energyexemplar.com

 

 

Hammoq Inc is a rapidly growing startup in the reselling sector. Our app provides product listings, cross-platform data analytics, and Cross-platform delisting as our core services.

Launched Web app in 2020 and iOS app at the start of 2021, we are continuing our exponential growth, and we were hoping you could play a core role in our mission.

Hammoq is looking for a Senior ML/Machine Vision Architect / Researcher, an expert in Deep Learning, to join our passionate developers' team to create our unique SaaS web app.

The ideal candidate will be responsible for developing new Machine Learning / Machine vision models according to the business needs. 

*What you'll do

• You’ll lead the ML R&D process at Hammoq.
• You will build ML architectures to optimise the process. 
• You'll collaborate with our hardworking, nimble, and supportive team through daily standups, company presentations, product demos, slack discussions
• You'll work on solving machine vision / Machine Learning problems and implementations.
• You'll use ML libraries of IOS and Android to build and run models on the mobile devices

Skills and expertise that will help you succeed

• Must have experience working with OpenCV, TensorFlow, and Keras environment 
• Must have the ability to develop your own models.
• Working experience of training and deploying computer vision models  
• Experience in Computer Vision and Machine Learning (including Deep Learning) algorithms. 
• Experience in image analytics - including feature extraction, object detection, classification, and tracking 
• Experience in image manipulation
• PhD in Computer Vision , Machine Learning, Machine Vision or any related field is a must.
• Strong programming skills in Python, including NumPy, Scikit Learn, Pandas, and Matplotlib 
• Self-governing analytical problem-solving skills for efficient and uninterrupted development of solutions
• Strong communications skills for an adequate description of technical concepts to others

Nice to have

• Experience in building APIs implementing ML models
• Knowledge or basic understanding of any Cloud ML technologies or Cloud ML service providers.
• Experience in the e-commerce industry

As a Senior Engineer - Big Data Analytics, you will help the architectural design and development for Healthcare Platforms, Products, Services, and Tools to deliver the vision of the Company. You will significantly contribute to engineering, technology, and platform architecture. This will be done through innovation and collaboration with engineering teams and related business functions. This is a critical, highly visible role within the company that has the potential to drive significant business impact. 

The scope of this role will include strong technical contribution in the development and delivery of Big Data Analytics Cloud Platform, Products and Services in collaboration with execution and strategic partners. 

 

Responsibilities:

• Design & develop, operate, and drive scalable, resilient, and cloud native Big Data Analytics platform to address the business requirements
• Help drive technology transformation to achieve business transformation, through the creation of the Healthcare Analytics Data Cloud that will help Change establish a leadership position in healthcare data & analytics in the industry
• Help in successful implementation of Analytics as a Service 
• Ensure Platforms and Services meet SLA requirements
• Be a significant contributor and partner in the development and execution of the Enterprise Technology Strategy

 

Qualifications:

• At least 2 years of experience software development for big data analytics, and cloud. At least 5 years of experience in software development
• Experience working with High Performance Distributed Computing Systems in public and private cloud environments
• Understands big data open-source eco-systems and its players. Contribution to open source is a strong plus
• Experience with Spark, Spark Streaming, Hadoop, AWS/Azure, NoSQL Databases, In-Memory caches, distributed computing, Kafka, OLAP stores, etc.
• Have successful track record of creating working Big Data stack that aligned with business needs, and delivered timely enterprise class products
• Experience with delivering and managing scale of Operating Environment
• Experience with Big Data/Micro Service based Systems, SaaS, PaaS, and Architectures
• Experience Developing Systems in Java, Python, Unix
• BSCS, BSEE or equivalent, MSCS preferred

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Data Engineer

• Drive the data engineering implementation
• Strong experience in building data pipelines
• AWS stack experience is must
• Deliver Conceptual, Logical and Physical data models for the implementation
teams.

• SQL stronghold is must. Advanced SQL working knowledge and experience
working with a variety of relational databases, SQL query authoring
• AWS Cloud data pipeline experience is must. Data pipelines and data centric
applications using distributed storage platforms like S3 and distributed processing
platforms like Spark, Airflow, Kafka
• Working knowledge of AWS technologies such as S3, EC2, EMR, RDS, Lambda,
Elasticsearch
• Ability to use a major programming (e.g. Python /Java) to process data for
modelling.

• Model design, feature planning, system infrastructure, production setup and monitoring, and release management. 
• Excellent understanding of machine learning techniques and algorithms, such as SVM, Decision Forests, k-NN, Naive Bayes etc.
• Experience in selecting features, building and optimizing classifiers using machine learning techniques.
• Prior experience with data visualization tools, such as D3.js, GGplot, etc..
• Good knowledge on statistics skills, such as distributions, statistical testing, regression, etc..
• Adequate presentation and communication skills to explain results and methodologies to non-technical stakeholders.
• Basic understanding of the banking industry is value add

Develop, process, cleanse and enhance data collection procedures from multiple data sources.
• Conduct & deliver experiments and proof of concepts to validate business ideas and potential value.
• Test, troubleshoot and enhance the developed models in a distributed environments to improve it's accuracy.
• Work closely with product teams to implement algorithms with Python and/or R.
• Design and implement scalable predictive models, classifiers leveraging machine learning, data regression.
• Facilitate integration with enterprise applications using APIs to enrich implementations