Data Engineer (1555) (offline)
Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and programming. If you also have knowledge of data science and software engineering, we’d like to meet you.
About Our Customer:
The customer is a leader in actionable analytics or sales effectiveness. It is revolutionizing how field sales teams make their day-to-day decisions, providing them with real-time, in-context, and in-workflow smart suggestions that have been shown to meaningfully improve rep performance. Smart suggestions, driven by data, help reps better navigate sales decisions such as which prospects to call, when and where to call on them, what products to position, which messages to use, and why.
About Our Project:
The Customer provides a salesforce data based intelligence platform, that analyzes all daily activity of pharmaceutical company representatives around all regions, providing intelligent suggestions of actions to boost engagements and sales. Historically, 100% of suggestions were done using statically coded business rules, defined per customer. Now, the system is getting ML-driven enhancements on top of those static rules. For example, the business rules engine decides that it is time to send an email to a health care provider (HCP), but ML models decide which template is more likely to appeal to a given HCP and on which days they most often open promotional materials as opposed to the days they never read them. The same can be done in regards to personal visits, medical conferences invites, etc.
ML modules in the Customer’s company are undergoing real case-studies after deployment to prove the concept. And the results are driving real-world engagement increase. For reference - "just" 4% engagement increase (from one of the studies) is a huge win in a multi-billion and highly competitive industry.
Our ideal candidate will have extensive knowledge of Big Data and ML; specifically, how to organize and architect ML modules. Our ML-specialized team only works on ML projects and has active and case-studies proven ML modules in production (and is working on new ones all the time). We're looking for a talented professional to bring strong architectural advice to the table.
Project Team:
This is a dedicated scrum team with about 5 engineers (several ML-related PhDs among them), 2 QAs, and a scrum master.
Requirements:
- 3-5 years of relevant experience with a proven track record of developing algorithms and machine learning products for production-ready recommendation or prediction systems using languages and big data platforms such as Scala, Python, R, Java, Spark, Cassandra, and Hadoop.
- Deep understanding and experience in big data concepts
- Extensive knowledge of ML frameworks, libraries (e.g. Scikit, Numpy, Pandas, TensorFlow, R ML packages), tools (AWS EMR, Databricks, Knime, etc), data structures, and data modeling concepts
- Able to organize and architect ML modules
- Knowledge of mathematics, statistics, and algorithms (Random Forests, General Linear Regression, Elastic Nets, Clustering, and NLP)
- Design/use schemas in various data storage platforms (MySQL, DataLake, S3, Snowflake)
- Experience in design/development of RESTful APIs in Java(Spring)
Nice to have:
- Superb analytical and problem-solving abilities
- Great communication, collaboration skills, time management, and organizational abilities
- BS/MS in computer science, ML, mathematics, or related field and/or equivalent work experience
- Lead role in one or more projects, architecting/designing middle-tier, ML, or database layers for a new application.
- Software engineers with experience working with machine learning applications
- Math background and understanding of algorithms is a plus
Responsibilities:
- Analyze and improve existing data science modules
- Design new machine learning modules according to requirements
- Research and advise on appropriate ML algorithms, tools and integration/deployment strategies
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Use test results to perform statistical analysis and fine-tuning
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
- Keep abreast of developments in the field
50% - Take new moled that Data Science team has created and productize it
25% - enhance the model, working with data science team
25% - engineering - supporting qa, docs ect
Company offers:
- Vacation is 20 working days / till 20 working days per year for sick leaves
- Full payment of taxes
- English courses
- Flexible work schedule
- Friendly environment
- Medical insurance
- Opportunity for career growth
About Our Customer:
The customer is a leader in actionable analytics or sales effectiveness. It is revolutionizing how field sales teams make their day-to-day decisions, providing them with real-time, in-context, and in-workflow smart suggestions that have been shown to meaningfully improve rep performance. Smart suggestions, driven by data, help reps better navigate sales decisions such as which prospects to call, when and where to call on them, what products to position, which messages to use, and why.
About Our Project:
The Customer provides a salesforce data based intelligence platform, that analyzes all daily activity of pharmaceutical company representatives around all regions, providing intelligent suggestions of actions to boost engagements and sales. Historically, 100% of suggestions were done using statically coded business rules, defined per customer. Now, the system is getting ML-driven enhancements on top of those static rules. For example, the business rules engine decides that it is time to send an email to a health care provider (HCP), but ML models decide which template is more likely to appeal to a given HCP and on which days they most often open promotional materials as opposed to the days they never read them. The same can be done in regards to personal visits, medical conferences invites, etc.
ML modules in the Customer’s company are undergoing real case-studies after deployment to prove the concept. And the results are driving real-world engagement increase. For reference - "just" 4% engagement increase (from one of the studies) is a huge win in a multi-billion and highly competitive industry.
Our ideal candidate will have extensive knowledge of Big Data and ML; specifically, how to organize and architect ML modules. Our ML-specialized team only works on ML projects and has active and case-studies proven ML modules in production (and is working on new ones all the time). We're looking for a talented professional to bring strong architectural advice to the table.
Project Team:
This is a dedicated scrum team with about 5 engineers (several ML-related PhDs among them), 2 QAs, and a scrum master.
Requirements:
- 3-5 years of relevant experience with a proven track record of developing algorithms and machine learning products for production-ready recommendation or prediction systems using languages and big data platforms such as Scala, Python, R, Java, Spark, Cassandra, and Hadoop.
- Deep understanding and experience in big data concepts
- Extensive knowledge of ML frameworks, libraries (e.g. Scikit, Numpy, Pandas, TensorFlow, R ML packages), tools (AWS EMR, Databricks, Knime, etc), data structures, and data modeling concepts
- Able to organize and architect ML modules
- Knowledge of mathematics, statistics, and algorithms (Random Forests, General Linear Regression, Elastic Nets, Clustering, and NLP)
- Design/use schemas in various data storage platforms (MySQL, DataLake, S3, Snowflake)
- Experience in design/development of RESTful APIs in Java(Spring)
Nice to have:
- Superb analytical and problem-solving abilities
- Great communication, collaboration skills, time management, and organizational abilities
- BS/MS in computer science, ML, mathematics, or related field and/or equivalent work experience
- Lead role in one or more projects, architecting/designing middle-tier, ML, or database layers for a new application.
- Software engineers with experience working with machine learning applications
- Math background and understanding of algorithms is a plus
Responsibilities:
- Analyze and improve existing data science modules
- Design new machine learning modules according to requirements
- Research and advise on appropriate ML algorithms, tools and integration/deployment strategies
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Use test results to perform statistical analysis and fine-tuning
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
- Keep abreast of developments in the field
50% - Take new moled that Data Science team has created and productize it
25% - enhance the model, working with data science team
25% - engineering - supporting qa, docs ect
Company offers:
- Vacation is 20 working days / till 20 working days per year for sick leaves
- Full payment of taxes
- English courses
- Flexible work schedule
- Friendly environment
- Medical insurance
- Opportunity for career growth
About Exadel
For more than 20 years, Exadel has been delivering Digital Transformation services, enterprise and custom software solutions for Fortune 500 clients, including HPE, Deloitte, Home Depot and McKesson. With 20+ locations and delivery centers across the US and Europe, Exadel solves the most complex engineering problems using Agile methodologies, offering a scalable and skilled mix of multi-shore resources at the industry's most competitive price. Exadel’s digital transformation solutions and services help chart new strategies that are built upon creative thinking, cutting-edge design, and technical innovation, designed for the growing digital landscape of business.Enterprise Services
- Digital Transformation Experts
- Developing mission-critical software and mobile applications
- Advising companies on how best to leverage open source technology
- Helping companies plan and implement migrations to better technology stacks
- Providing QA, automation, and testing services for application development
- Supporting and maintaining applications and systems for companies
- Providing on-line training and mentoring to companies
- Assisting companies in evaluating their current enterprise software architecture and planning for improvements or new systems.
Company website:
https://exadel.com/
DOU company page:
https://jobs.dou.ua/companies/exadel/
The job ad is no longer active
Job unpublished on
4 January 2022
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