Machine Learning Ops Engineer

Senior Executive - Analytics

Overview of job :-

Our Client is the world’s largest media investment company which is a part of WPP. They are a global digital transformation agency with 1200 employees across 21 nations. Our team of experts support clients in programmatic, social, paid search, analytics, technology, organic search, affiliate marketing, e-commerce and across traditional channels.

We are currently looking for a Sr Executive – Analytics to join us. In this role, you will be responsible for a massive opportunity to build and be a part of largest performance marketing setup APAC is committed to fostering a culture of diversity and inclusion. Our people are our strength so we respect and nurture their individual talent and potential.

Reporting of the role - This role reports to the Director - Analytics,

3 best things about the job:

1. Responsible for data & analytics projects and developing data strategies by diving into data and extrapolating insights and providing guidance to clients

2. Build and be a part of a dynamic team

3. Being part of a global organisations with rapid growth opportunities

Responsibilities of the role:

 Build Marketing-Mix and Multi-Touch attribution models using a range of tools, including free and paid.

 Work with large data sets via hands-on data processing to produce structured data sets for analysis.

 Design and build Visualization, Dashboard and reports for both Internal and external clients using Tableau, Power BI, Datorama or R Shiny/Python.

What you will need:

 Degree in Mathematics, Statistics, Economics, Engineering, Data Science, Computer Science or quantitative field.

 2-3 years’ experience in Marketing/Data Analytics or related field with hands-on experience in building Marketing-Mix and Attribution models.  Proficiency in one or more coding languages – preferred languages: Python, R

 Proficiency in one or more Visualization Tools – Tableau, Datorama, Power BI

 Proficiency in using SQL.

 Proficiency with one or more statistical tools is a plus – Example: SPSS, SAS, MATLAB, Mathcad.

 Working experience using big data technologies (Hive/Hadoop) is a plus

🚀 Exciting Opportunity: Data Engineer Position in Gurugram 🌐

Hello 

We are actively seeking a talented and experienced Data Engineer to join our dynamic team at Reality Motivational Venture in Gurugram (Gurgaon). If you're passionate about data, thrive in a collaborative environment, and possess the skills we're looking for, we want to hear from you!

Position: Data Engineer  

Location: Gurugram (Gurgaon)  

Experience: 5+ years 

Key Skills:

- Python

- Spark, Pyspark

- Data Governance

- Cloud (AWS/Azure/GCP)

Main Responsibilities:

- Define and set up analytics environments for "Big Data" applications in collaboration with domain experts.

- Implement ETL processes for telemetry-based and stationary test data.

- Support in defining data governance, including data lifecycle management.

- Develop large-scale data processing engines and real-time search and analytics based on time series data.

- Ensure technical, methodological, and quality aspects.

- Support CI/CD processes.

- Foster know-how development and transfer, continuous improvement of leading technologies within Data Engineering.

- Collaborate with solution architects on the development of complex on-premise, hybrid, and cloud solution architectures.

Qualification Requirements:

- BSc, MSc, MEng, or PhD in Computer Science, Informatics/Telematics, Mathematics/Statistics, or a comparable engineering degree.

- Proficiency in Python and the PyData stack (Pandas/Numpy).

- Experience in high-level programming languages (C#/C++/Java).

- Familiarity with scalable processing environments like Dask (or Spark).

- Proficient in Linux and scripting languages (Bash Scripts).

- Experience in containerization and orchestration of containerized services (Kubernetes).

- Education in database technologies (SQL/OLAP and Non-SQL).

- Interest in Big Data storage technologies (Elastic, ClickHouse).

- Familiarity with Cloud technologies (Azure, AWS, GCP).

- Fluent English communication skills (speaking and writing).

- Ability to work constructively with a global team.

- Willingness to travel for business trips during development projects.

Preferable:

- Working knowledge of vehicle architectures, communication, and components.

- Experience in additional programming languages (C#/C++/Java, R, Scala, MATLAB).

- Experience in time-series processing.

How to Apply:

Interested candidates, please share your updated CV/resume with me.

Thank you for considering this exciting opportunity.

Data Engineer- Senior

Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.

What are you going to do?

Design & Develop high performance and scalable solutions that meet the needs of our customers.

Closely work with the Product Management, Architects and cross functional teams.

Build and deploy large-scale systems in Java/Python.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Create data tools for analytics and data scientist team members that assist them in building and optimizing their algorithms.

Follow best practices that can be adopted in Bigdata stack.

Use your engineering experience and technical skills to drive the features and mentor the engineers.

What are we looking for ( Competencies) :

Bachelor’s degree in computer science, computer engineering, or related technical discipline.

Overall 5 to 8 years of programming experience in Java, Python including object-oriented design.

Data handling frameworks: Should have a working knowledge of one or more data handling frameworks like- Hive, Spark, Storm, Flink, Beam, Airflow, Nifi etc.

Data Infrastructure: Should have experience in building, deploying and maintaining applications on popular cloud infrastructure like AWS, GCP etc.

Data Store: Must have expertise in one of general-purpose No-SQL data stores like Elasticsearch, MongoDB, Redis, RedShift, etc.

Strong sense of ownership, focus on quality, responsiveness, efficiency, and innovation.

Ability to work with distributed teams in a collaborative and productive manner.

Benefits:

Competitive Salary Packages and benefits.

Collaborative, lively and an upbeat work environment with young professionals.

Job Category: Development

Job Type: Full Time

Job Location: Bangalore

- Modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, mining, and visualization techniques

- Experience working with business understanding the requirement, creating the problem statement, and building scalable and dependable Analytical solutions

- Must have hands-on and strong experience in Python

- Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning

- Strong analytical & algorithm development skills

- Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining, etc

- Ability to collaborate across teams and strong interpersonal skills

Skills

- Sound theoretical knowledge in ML algorithm and their application

- Hands-on experience in statistical modeling tools such as R, Python, and SQL

- Hands-on experience in Machine learning/data science

- Strong knowledge of statistics

- Experience in advanced analytics / Statistical techniques – Regression, Decision trees, Ensemble machine learning algorithms, etc

- Experience in Natural Language Processing & Deep Learning techniques 

- Pandas, NLTK, Scikit-learn, SpaCy, Tensorflow

Roles & Responsibilities

• Designing and delivering a best-in-class, highly scalable data governance platform
• Improving processes and applying best practices
• Contribute in all scrum ceremonies; assuming the role of ‘scum master’ on a rotational basis
•  Development, management and operation of our infrastructure to ensure it is easy to deploy, scalable, secure and fault-tolerant
• Flexible on working hours as per business needs

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