Python Developer

About DeepIntent:

DeepIntent is a marketing technology company that helps healthcare brands strengthen communication with patients and healthcare professionals by enabling highly effective and performant digital advertising campaigns. Our healthcare technology platform, MarketMatch™, connects advertisers, data providers, and publishers to operate the first unified, programmatic marketplace for healthcare marketers. The platform’s built-in identity solution matches digital IDs with clinical, behavioural, and contextual data in real-time so marketers can qualify 1.6M+ verified HCPs and 225M+ patients to find their most clinically-relevant audiences and message them on a one-to-one basis in a privacy-compliant way. Healthcare marketers use MarketMatch to plan, activate, and measure digital campaigns in ways that best suit their business, from managed service engagements to technical integration or self-service solutions. DeepIntent was founded by Memorial Sloan Kettering alumni in 2016 and acquired by Propel Media, Inc. in 2017. We proudly serve major pharmaceutical and Fortune 500 companies out of our offices in New York, Bosnia and India.

What You’ll Do:

• Establish formal data practice for the organisation.
• Build & operate scalable and robust data architectures.
• Create pipelines for the self-service introduction and usage of new data
• Implement DataOps practices
• Design, Develop, and operate Data Pipelines which support Data scientists and machine learning
• Engineers.
• Build simple, highly reliable Data storage, ingestion, and transformation solutions which are easy
• to deploy and manage.
• Collaborate with various business stakeholders, software engineers, machine learning
• engineers, and analysts.

Who You Are:

• Experience in designing, developing and operating configurable Data pipelines serving high
• volume and velocity data.
• Experience working with public clouds like GCP/AWS.
• Good understanding of software engineering, DataOps, data architecture, Agile and
• DevOps methodologies.
• Experience building Data architectures that optimize performance and cost, whether the
• components are prepackaged or homegrown
• Proficient with SQL, Java, Spring boot, Python or JVM-based language, Bash
• Experience with any of Apache open source projects such as Spark, Druid, Beam, Airflow
• etc. and big data databases like BigQuery, Clickhouse, etc
• Good communication skills with the ability to collaborate with both technical and non-technical
• people.
• Ability to Think Big, take bets and innovate, Dive Deep, Bias for Action, Hire and Develop the Best, Learn and be Curious

Data Scientist-

We are looking for an experienced Data Scientists to join our engineering team and

help us enhance our mobile application with data. In this role, we're looking for

people who are passionate about developing ML/AI in various domains that solves

enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering

problems.

As one of the earliest members in engineering, you will have the flexibility to design

the models and architecture from ground up. As any early-stage start-up, we expect

you to be comfortable wearing various hats, and be proactive contributor in building

something truly remarkable.

Responsibilities

Researches, develops and maintains machine learning and statistical models for

business requirements

Work across the spectrum of statistical modelling including supervised,

unsupervised, & deep learning techniques to apply the right level of solution to

the right problem Coordinate with different functional teams to monitor outcomes and refine/

improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation

Identify unexplored data opportunities for the business to unlock and maximize

the potential of digital data within the organization

Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data

Qualifications

3+ years of experience solving complex business problems using machine

learning.

Fluency in programming languages such as Python, NLP and Bert, is a must

Strong analytical and critical thinking skills

Experience in building production quality models using state-of-the-art technologies 

Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is

desirable Ability to collaborate on projects and work independently when required.

Previous experience in Fintech/payments domain is a bonus

You should have Bachelor’s or Master’s degree in Computer Science, Statistics

or Mathematics or another quantitative field from a top tier Institute

About Quadratyx:

We are a product-centric insight & automation services company globally. We help the world’s organizations make better & faster decisions using the power of insight & intelligent automation. We build and operationalize their next-gen strategy, through Big Data, Artificial Intelligence, Machine Learning, Unstructured Data Processing and Advanced Analytics. Quadratyx can boast more extensive experience in data sciences & analytics than most other companies in India.

We firmly believe in Excellence Everywhere.

Job Description

Purpose of the Job/ Role:

• As a Technical Lead, your work is a combination of hands-on contribution, customer engagement and technical team management. Overall, you’ll design, architect, deploy and maintain big data solutions.

Key Requisites:

• Expertise in Data structures and algorithms.

• Technical management across the full life cycle of big data (Hadoop) projects from requirement gathering and analysis to platform selection, design of the architecture and deployment.

• Scaling of cloud-based infrastructure.

• Collaborating with business consultants, data scientists, engineers and developers to develop data solutions.

• Led and mentored a team of data engineers.

• Hands-on experience in test-driven development (TDD).

• Expertise in No SQL like Mongo, Cassandra etc, preferred Mongo and strong knowledge of relational databases.

• Good knowledge of Kafka and Spark Streaming internal architecture.

• Good knowledge of any Application Servers.

• Extensive knowledge of big data platforms like Hadoop; Hortonworks etc.

• Knowledge of data ingestion and integration on cloud services such as AWS; Google Cloud; Azure etc. 

Skills/ Competencies Required

Technical Skills

• Strong expertise (9 or more out of 10) in at least one modern programming language, like Python, or Java.

• Clear end-to-end experience in designing, programming, and implementing large software systems.

• Passion and analytical abilities to solve complex problems Soft Skills.

• Always speaking your mind freely.

• Communicating ideas clearly in talking and writing, integrity to never copy or plagiarize intellectual property of others.

• Exercising discretion and independent judgment where needed in performing duties; not needing micro-management, maintaining high professional standards.

Academic Qualifications & Experience Required

Required Educational Qualification & Relevant Experience

• Bachelor’s or Master’s in Computer Science, Computer Engineering, or related discipline from a well-known institute.

• Minimum 7 - 10 years of work experience as a developer in an IT organization (preferably Analytics / Big Data/ Data Science / AI background.

• Play a critical role as a member of the leadership team in shaping and supporting our overall company vision, day-to-day operations, and culture.
• Set the technical vision and build the technical product roadmap from launch to scale; including defining long-term goals and strategies
• Define best practices around coding methodologies, software development, and quality assurance
• Define innovative technical requirements and systems while balancing time, feasibility, cost and customer experience
• Build and support production products
• Ensure our internal processes and services comply with privacy and security regulations
• Establish a high performing, inclusive engineering culture focused on innovation, execution, growth and development
• Set a high bar for our overall engineering practices in support of our mission and goals
• Develop goals, roadmaps and delivery dates to help us scale quickly and sustainably
• Collaborate closely with Product, Business, Marketing and Data Science
• Experience with financial and transactional systems
• Experience engineering for large volumes of data at scale
• Experience with financial audit and compliance is a plus
• Experience building a successful consumer facing web and mobile apps at scale

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