DCY is seeking a talented and motivated ML Engineer, Researcher in Signal domain. DCY is the corporate research division that focuses on advanced technology development for applications across all DCY product lines including Automotive, Lifestyle (consumer), and Professional.

The Machine Learning Engineer will be responsible for the development for advanced car driver state analysis systems.

You will be responsible for translating complex analytical concepts into actionable results for our research. As a Data Scientist on the DCY Neurosense team, you will work with a world-class multidisciplinary team to deploy scalable predictive reasoning and data mining algorithms, as well as extract / transform Big Data. Provide technical expertise and business consultative skills to address supervised and unsupervised learning problems in an applied automotive analytics environments. You will also be directly responsible for preparing, analyzing and generating effective project results in an efficient and errorless manner using classical statistical techniques as well as advanced tools, delivered on time and on budget.

This position will be located in Yerevan, Armenia, where the successful candidate will have access to world class tools and facilities.

This position has no direct reports.

• Work with state-of-the-art neural network models for Signals (some times computer vision) and biometrics
• Work with biosignals such as heart rate/ECG/32 channel EEG
• Work with big car data from a multitude of sensors
• Select statistical, machine learning and artificial intelligence algorithms to solve filtering, clustering and classification problems.
• Work with time series, knowledge of spectral and non-linear ways of representing signals.
• Handle large-scale data sets and organization of relevant data
• Work closely with other senior machine learning researchers and engineers in autonomy
• As part of a matrix organization work with engineers, designers, testers and managers as needed to help integrate, evaluate and productize your solutions
• Perform code reviews and other activities to ensure high-quality results
• Analyze, write and adapt software requirements
• Provide data/report support for complex data mining projects.
• Conceptualize problems, apply appropriate theory, explore approaches, simulate, and implement with minimal supervision.
• Define data needs, evaluate data quality, and extract/transform data for analytic projects and research.
  

• Master Degree or higher in Physics, Mathematics, Computer Science or related field.
• Must have 5+ years’ experience in Predictive Modeling & Data Mining; Competitive/Customer Intelligence; Statistical Model Development; Analytics (Predictive Analytics); Big Data; and High Performance Computing
• 3+ years experience working in the field of machine learning for computer vision or biosignal analysis.
• NumPy, Pandas, etc.to dig into data to extract meaning from information.
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Experience with common data science toolkits, such a NumPy
• Experience with data visualization tools, such as Plotly
• Proficiency in using query languages such as SQL
• Hands-on experience in applied Machine Learning along with deep learning experience with frameworks, preferably pytorch.
• Proficient in one or more relevant programming languages: Python
• Enterprise level documentation skills
• Developed soft skills. Ability to arrange work in small groups of reporting engineers.
• Experience working with large volumes of data, preferably in auto, or healthcare
• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Must be able to identify data relationships, trends, and anomalies.
• Strong written and verbal communication skills.
• Ability to interpret and articulate analytical results 

• Ability to show value of analytics within business processes
• Regression (linear, logistic, multinomial, censored)
• Test Design/Design of Experiments
• Segmentation and clustering
• Decision tree analysis
• Mathematical programming and optimization
• Optimization