Lead Data Scientist from home | EPAM Anywhere
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Lead Data Scientist for a Vaccine Company

Lead Data Scientist for a Vaccine Company 40 hrs/week, 12+ months

A remote Lead Data Scientist is needed. This job is about turning (big) data into actionable knowledge, which requires a blend of scientific, problem solving, analytical, technical, and communication skills.

The customer is a global influenza vaccine company developing innovative solutions to ensure epidemic and pandemic preparedness throughout the world.

Responsibilities

  • Lead strategic planning, development and implementation of medium-to-large data science solutions or a component of a larger solution, including predictive modeling, unsupervised and supervised learning, and machine learning techniques
    • Lead on all stages of presales activities for such projects, owning the whole presale process from the Competency Center perspective when required. Manage the delivery of architectural POCs, where required
      • Interact with clients, advise and drive the translation of business requirements and models into appropriate architectural designs to ensure that business needs are met
        • Work directly and collaboratively with clients, external data providers, and other key stakeholders to ensure that the solution’s concept/vision is understood and agreed upon
          • Actively participate in project review and planning sessions. As needed, lead the solution development, drive and supervise end-to-end development cycle (SDLC) or participate in the projects start-up
            • Be accountable for applications-related quality, performance, availability, scalability, security, and integrity, ensuring application usability, for instance, through a high-quality functional interface to applications. Identify and mitigate risks associated with specific solution in known contexts
              • Be accountable for ensuring architectural consistency of recommended technology and its integration with the client’s applications and infrastructure. Identify and mitigate risks associated the implemented solution in all relevant contexts of the project and wider program
                • Manage the architectural knowledge transfer from the project development team to the post-go-live support team. Oversea or effect the creation of architectural case study for EPAM’s repository of reusable assets
                  • Drive strategic visioning activities for the practice and competency center. Develop reusable assets, development methods, processes, best practices to accelerate delivery. Coordinate SA pool on those activities
                    • Drive the program of evaluating the hardware and software platforms, benchmarking of alternative solution architectures, supervise a defined process for provision of structured, reusable results. Coordinate the direction of R&D activities by SA pool
                      • Keep pace with the innovative technologies and consider possibilities of creating relevant solution offerings. Coordinate architects in developmental direction choice
                        • Consult and supervise all team members, share knowledge. Participate in the assessment of the candidates for SA position. Mentor other solution architects in practical SA activities. Provide technical guidance and career-planning assistance
                          • Write broad topic and strategic white papers in the course of industry and technology research. Maintain high competency visibility by regular posting in internal newsletters, blogs as well as speaking at internal and external conferences and other events; create blueprints on customer request. Create technology road
                            • Analyze large data sets to discover trends, identify performance metrics, and uncover optimization opportunities
                              • Apply machine learning algorithms and statistical methods to large sets of raw data
                                • Continuously improve algorithms and develop best practice for instrumentation
                                  • Work to acquire enterprise architecture theoretical knowledge
                                    • Should be able to

                                      Requirements

                                      • RDBMS/SQL knowledge
                                        • Programming experience (Python preferred)
                                          • Data analysis tools and libraries such as Python (NumPy / SciPy / scikit-learn / pandas / matplotlib), R, SAS, SPSS, MATLAB, etc.
                                            • Big Data stack; Spark / MLlib
                                              • Proficiency with at least one of the Cloud providers
                                                • Experience with Data Science solutions productionalization
                                                  • Data visualization skills
                                                    • NLP/text mining
                                                      • Bachelor’s/Master’s Degree in Computer Science, Math, Applied Statistics or a related field
                                                        • A few years of experience in data mining, statistics or machine learning
                                                          • In-depth domain understanding and ability to acquire new domain knowledge
                                                            • Aptitude for problem solving
                                                              • Data focused applied mathematics (statistical analysis, machine learning)
                                                                • Decent communication / presentation skills (including working English fluency)

                                                                  Nice to have

                                                                  • Platforms: Linux, Windows
                                                                    • Programming Languages: Python, R, SQL
                                                                      • Python libraries: scikit-learn, pandas, NumPy, SciPy, matplotlib, seaborn
                                                                        • Deep Learning: Keras, TensorFlow, PyTorch
                                                                          • Big Data: Spark, Hadoop, Hive
                                                                            • Cloud: AWS/Azure/GCP - Storage; Compute; Networking; Identity and Security; Notebooks; Data Catalogs
                                                                              • CI/CD principles & tools (e.g. Jenkins)
                                                                                • Version Control Systems (e.g. Git, SVN)

                                                                                  Benefits in eligible locations

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                                                                                  For you

                                                                                  • Voluntary health insurance for you (100% covered) and your family (with corporate discount)
                                                                                  • Individual sessions with professional psychologists and coaches
                                                                                  • Free corporate sports and wellness programs
                                                                                  • Stable income
                                                                                  • Paid time off
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                                                                                  For your comfortable work

                                                                                  • 100% remote work forever
                                                                                  • Free licensed software
                                                                                  • Possibility to work on your own device (BYOD)
                                                                                  • Stable workload
                                                                                  • Relocation opportunities
                                                                                  • Flexible engagement models
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                                                                                    For your growth

                                                                                    • Free trainings for technical and soft skills
                                                                                    • Access to LinkedIn Learning platform
                                                                                    • Language courses
                                                                                    • Access to internal and external e-Libraries
                                                                                    • Certification opportunities
                                                                                    • Skill advisory service

                                                                                      40 hrs/week

                                                                                      Hours per week

                                                                                      12+ months

                                                                                      Project length

                                                                                      Belarus, Russia, Ukraine

                                                                                      Locations eligible for the position