Area Business Manager

1. Design, develop, and maintain data pipelines using Azure Data Factory

2. ⁠Create and manage data models in PostgreSQL, ensuring efficient data storage and retrieval.

3. ⁠Optimize query performance and database performance in PostgreSQL, including indexing, query tuning, and performance monitoring.

4. Strong knowledge on data modeling and mapping from various sources to data model.

5. ⁠Develop and maintain logging mechanisms in Azure Data Factory to monitor and troubleshoot data pipelines.

6. Strong knowledge on Key Vault, Azure Data lake, PostgreSQL

7. ⁠Manage file handling within Azure Data Factory, including reading, writing, and transforming data from various file formats.

8. Strong SQL query skills with the ability to handle multiple scenarios and optimize query performance.

9. ⁠Excellent problem-solving skills and ability to handle complex data scenarios.

10. Collaborate with Business stakeholder, data architects and PO's to understand and meet their data requirements.

11. Ensure data quality and integrity through validation and quality checks.

12. Having Power BI knowledge, creating and configuring semantic models & reports would be preferred.

Job Description:

We are seeking a Senior AI Developer to join our dynamic team and lead AI-driven projects. This role requires a blend of advanced technical expertise in AI and machine learning, exceptional problem-solving abilities, and experience in building and deploying scalable AI solutions.

Key Responsibilities:

• Machine Learning & AI: Expertise in ML algorithms, especially for classification, anomaly detection, and predictive analytics.
• Cloud Platforms: Proficiency in Google Cloud Platform (GCP) services, including Cloud Run, BigQuery, and Vertex AI.
• Programming Languages: Advanced knowledge of Python; experience with libraries like TensorFlow, PyTorch, Scikit-learn, and Pandas.
• Data Processing: Skilled in SQL, data transformations, and ETL processes, especially with BigQuery.
• Anomaly Detection: Proven experience in building and deploying anomaly detection models, particularly for network data.
• Network Data Analysis: Familiarity with analyzing network logs, IP traffic, and related data structures.
• DevOps & CI/CD: Experience with CI/CD pipelines for ML model deployment, particularly with tools like Cloud Build.

Job Summary:

We are looking for an experienced Java Developer with 4+years of hands-on experience to join our dynamic team. The ideal candidate will have a strong background in Java development, problem-solving skills, and the ability to work independently as well as part of a team. You will be responsible for designing, developing, and maintaining high-performance and scalable applications.

Key Responsibilities:

• Design, develop, test, and maintain Java-based applications.
• Write well-designed, efficient, and testable code following best software development practices.
• Troubleshoot and resolve technical issues during development and production support.
• Collaborate with cross-functional teams including QA, DevOps, and Product teams.
• Participate in code reviews and provide constructive feedback.
• Maintain proper documentation for code, processes, and configurations.
• Support deployment and post-deployment monitoring during night shift hours.

Required Skills:

• Strong programming skills in Java 8 or above.
• Experience with Spring Framework (Spring Boot, Spring MVC, etc.).
• Proficiency in RESTful APIs, Microservices Architecture, and Web Services.
• Familiarity with SQL and relational databases like MySQL, PostgreSQL, or Oracle.
• Hands-on experience with version control systems like Git.
• Understanding of Agile methodologies.
• Experience with build tools like Maven/Gradle.
• Knowledge of unit testing frameworks (JUnit/TestNG).

Preferred Skills (Good to Have):

• Experience with cloud platforms (AWS, Azure, or GCP).
• Familiarity with CI/CD pipelines.
• Basic understanding of frontend technologies like JavaScript, HTML, CSS.

• Reviewing application requirements and interface designs.
• Identifying web-based user interactions.
• Developing and implementing highly responsive user interface components using react concepts.
• Writing application interface codes using JavaScript following react.js workflows.
• Troubleshooting interface software and debugging application codes.
• Developing and implementing front-end architecture to support user interface concepts.
• Monitoring and improving front-end performance.
• Documenting application changes and developing updates.

Role and Responsibilities

• Execute data mining projects, training and deploying models over a typical duration of 2 -12 months.
• The ideal candidate should be able to innovate, analyze the customer requirement, develop a solution in the time box of the project plan, execute and deploy the solution.
• Integrate the data mining projects embedded data mining applications in the FogHorn platform (on Docker or Android).

Core Qualifications
Candidates must meet ALL of the following qualifications:

• Have analyzed, trained and deployed at least three data mining models in the past. If the candidate did not directly deploy their own models, they will have worked with others who have put their models into production. The models should have been validated as robust over at least an initial time period.
• Three years of industry work experience, developing data mining models which were deployed and used.
• Programming experience in Python is core using data mining related libraries like Scikit-Learn. Other relevant Python mining libraries include NumPy, SciPy and Pandas.
• Data mining algorithm experience in at least 3 algorithms across: prediction (statistical regression, neural nets, deep learning, decision trees, SVM, ensembles), clustering (k-means, DBSCAN or other) or Bayesian networks

Bonus Qualifications
Any of the following extra qualifications will make a candidate more competitive:

• Soft Skills
  • Sets expectations, develops project plans and meets expectations.
  • Experience adapting technical dialogue to the right level for the audience (i.e. executives) or specific jargon for a given vertical market and job function.
• Technical skills
  • Commonly, candidates have a MS or Ph.D. in Computer Science, Math, Statistics or an engineering technical discipline. BS candidates with experience are considered.
  • Have managed past models in production over their full life cycle until model replacement is needed. Have developed automated model refreshing on newer data. Have developed frameworks for model automation as a prototype for product.
  • Training or experience in Deep Learning, such as TensorFlow, Keras, convolutional neural networks (CNN) or Long Short Term Memory (LSTM) neural network architectures. If you don’t have deep learning experience, we will train you on the job.
  • Shrinking deep learning models, optimizing to speed up execution time of scoring or inference.
  • OpenCV or other image processing tools or libraries
  • Cloud computing: Google Cloud, Amazon AWS or Microsoft Azure. We have integration with Google Cloud and are working on other integrations.
  • Decision trees like XGBoost or Random Forests is helpful.
  • Complex Event Processing (CEP) or other streaming data as a data source for data mining analysis
  • Time series algorithms from ARIMA to LSTM to Digital Signal Processing (DSP).
  • Bayesian Networks (BN), a.k.a. Bayesian Belief Networks (BBN) or Graphical Belief Networks (GBN)
  • Experience with PMML is of interest (see www.DMG.org).
• Vertical experience in Industrial Internet of Things (IoT) applications:
  • Energy: Oil and Gas, Wind Turbines
  • Manufacturing: Motors, chemical processes, tools, automotive
  • Smart Cities: Elevators, cameras on population or cars, power grid
  • Transportation: Cars, truck fleets, trains

About FogHorn Systems
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT application solutions. FogHorn’s Lightning software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn’s technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.

Press:  https://www.foghorn.io/press-room/">https://www.foghorn.io/press-room/

Awards: https://www.foghorn.io/awards-and-recognition/">https://www.foghorn.io/awards-and-recognition/

• 2019 Edge Computing Company of the Year – Compass Intelligence
• 2019 Internet of Things 50: 10 Coolest Industrial IoT Companies – CRN
• 2018 IoT Planforms Leadership Award & Edge Computing Excellence – IoT Evolution World Magazine
• 2018 10 Hot IoT Startups to Watch – Network World. (Gartner estimated 20 billion connected things in use worldwide by 2020)
• 2018 Winner in Artificial Intelligence and Machine Learning – Globe Awards
• 2018 Ten Edge Computing Vendors to Watch – ZDNet & 451 Research
• 2018 The 10 Most Innovative AI Solution Providers – Insights Success
• 2018 The AI 100 – CB Insights
• 2017 Cool Vendor in IoT Edge Computing – Gartner
• 2017 20 Most Promising AI Service Providers – CIO Review

Our Series A round was for $15 million.  Our Series B round was for $30 million October 2017.  Investors include: Saudi Aramco Energy Ventures, Intel Capital, GE, Dell, Bosch, Honeywell and The Hive.

About the Data Science Solutions team
In 2018, our Data Science Solutions team grew from 4 to 9.  We are growing again from 11. We work on revenue generating projects for clients, such as predictive maintenance, time to failure, manufacturing defects.  About half of our projects have been related to vision recognition or deep learning. We are not only working on consulting projects but developing vertical solution applications that run on our Lightning platform, with embedded data mining.

Our data scientists like our team because:

• We care about “best practices”
• Have a direct impact on the company’s revenue
• Give or receive mentoring as part of the collaborative process
• Questions and challenging the status quo with data is safe
• Intellectual curiosity balanced with humility
• Present papers or projects in our “Thought Leadership” meeting series, to support continuous learning