Multinational company - leader in digital services is seeking an experienced Business Intelligence / Data Visualization Engineer to join a team passionate about data science and delivering cutting-edge visualizations & insights across the entire portfolio.

About the project:

This role will require working with internet-scale data across numerous product and customer touchpoints, undertaking in-depth quantitative analysis, and distilling data into actionable and intuitive visualizations to drive informed decision-making across all levels of the company.

About the team:

The team’s culture is centered around rapid iteration with open feedback and debate along the way. They encourage independent decision-making and taking calculated risks. Data Science & Analytics collaborates with partners across product, design, engineering, marketing, editorial, and business teams. They produce insights to drive decisions that enhance the customer experience, accelerate growth, and uncover new business opportunities while respecting user privacy.

Job Description:

• Build dashboards, self-service tools, and reports to analyze and present data associated with customer experience, product performance, business operations, and strategic decision-making.
• Create datasets, Develop global dashboards, data pipelines, sophisticated security controls, and scalable ad-hoc reporting
• Closely partner with the Data Science team to define metrics, datasets, and automation strategy.
• Engage with Product, Business, Engineering, and Marketing teams to capture requirements, influence how the services are measured, and craft world-class tools to support those partners.
• Establish a comprehensive roadmap to communicate and manage our commitments and stakeholder expectations while enabling org-wide transparency on progress.
• Focus on scale and efficiency - create and implement innovative solutions and establish best practices across our full scope of delivery

Key Qualifications:

• 5+ years of experience in a Data Visualization, Data Scientist, or Data Analyst role, preferably for a digital subscription business.
• Strong proficiency with SQL-based languages is required. Experience with large-scale data technologies such as Hadoop, PySpark
• Proficiency with data visualization tools such as Tableau, PowerBI, and Microstrategy for analysis, insight synthesis, data product delivery, and executive presentation.
• Education - minimum of a Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or related field.

Soft-skills:

• Curious business mindset with an ability to condense complex concepts and analysis into clear and concise takeaways that drive action.
• Excellent communication, social, and presentation skills with meticulous attention to detail.
• Strong time management skills with the ability to handle multiple projects with tight deadlines and executive visibility.
• Be known for successfully bridging analytics and business teams, with an ability to speak the language of both.
• Able to communicate and collaborate across many different teams, has an agile approach to solve challenging problems quickly, and stresses the details.

Location: CA, USA.

In search of a strong Data Scientist position on a long-term project of a large international company in the field of commercial and luxury residential real estate. 

Tasks:

• Analyze and process data. Identify anomalies, dependencies, trends, etc.;
• Collect and update analytical dashboards (Power BI, DataLens), visualize data and metrics;
• Formalize business objectives and generate hypotheses for research;
• Describe data warehousing change and optimization requirements;
• Select and optimize machine learning models to solve business problems;
• Present the results of your work and research.

We expect you to:

• Has been involved in analytics and Data Science for more than 3 years;
• Worked in a team, communicative and stress-resistant;
• want to understand data deeply and learn new things;
• worked with tasks from a business customer.

Skills:

• Are confident writing in Python and SQL;
• have good spreadsheet skills (excel, google);
• know how to apply ML in applied business tasks;
• know how to put forward analytical and product hypotheses, know how to organize and conduct experiments and interpret the results;
• know statistics;
• have experience with neural networks, generative machine learning models.

Level of Russian language: from B2.

We are looking for a skilled and motivated Bioinformatician / Data Scientist to join a dynamic team. In this role, you will have the opportunity to work on a diverse range of projects, utilizing your expertise in bioinformatics and data science to tackle complex scientific challenges. As a key member of our team, you will contribute to the development and application of cutting-edge computational methods and algorithms, enabling our clients to gain valuable insights from their data.

Should be able to be present in person at Cambridge, USA office at least once week.

Responsibilities:

• Collaborate closely with clients to understand their specific research goals and design tailored bioinformatics and data analysis solutions.
• Collaborate with interdisciplinary teams of biologists, geneticists, and data scientists to develop and implement computational strategies for analyzing large-scale biological datasets.
• Develop and implement computational pipelines and workflows for processing and analyzing diverse biological data types, including genomics, transcriptomics, proteomics, and metabolomics.
• Participation in development, deployment and optimization of bioinformatic workflows pipelines for processing NGS data (single-cell and bulk RNA-seq). Interpret results from these workflows to generate insights.
• Perform statistical analysis and data mining to identify patterns, correlations, and biomarkers.
• Apply statistical modeling and machine learning techniques to identify patterns, correlations, and predictive models from large-scale datasets.
• Stay up-to-date with the latest advancements in bioinformatics and contribute to the continuous improvement of existing methodologies and algorithms.
• Present findings and results to internal teams and external stakeholders in a clear and concise manner.
• Deploy and optimize bioinformatic workflows for the integration and analysis of NGS data, including short and long read sequencing data. Interpret results from these workflows to generate insights.
• Perform quality control checks, align sample data to the reference genome, and produce variants called files (VCFs), and joint-genotyped VCF files.
• Conduct statistical and genomic analysis, develop custom algorithms.

What we expect:

• B.S. or M.S. level of relevant education with hands on experience (Computer Science, Bioinformatics etc) in NGS workflow development and analysis.
• Experience with GxP, Genedata Selector and NGS for Cell Therapy domains is a must.
• Solid understanding of bioinformatics concepts, algorithms, and tools.
• Proven experience in analyzing high-throughput genomic, transcriptomic, or proteomic data.
• Hands-on experience with creating single-cell and bulk RNA-seq data processing pipelines.
• Proficiency in pipeline development using Nextflow, Cromwell, or other popular framework.
• Experience with Python programming language. Proficiency in programming languages such as Python or R and experience with relevant bioinformatics software and tools.
• Solid knowledge of statistical analysis, machine learning, and data mining techniques.
• English level C1 or higher.

Nice to have:

• Experience in next-generation sequencing (NGS) data analysis and variant calling.
• Knowledge of structural bioinformatics and molecular modeling.
• Familiarity with cloud computing platforms and big data analysis frameworks.
• Experience with deploying pipelines to AWS.
• Familiarity with cloud computing platforms and big data analysis frameworks.
• Strong communication and interpersonal skills with the ability to effectively collaborate with cross-functional teams and communicate complex concepts to non-technical stakeholders.

The project, a platform for creating and publishing content on social media using artificial intelligence tools, is looking for a Lead Data Engineer.

Responsibilities:

- Design, develop, and maintain robust and scalable data pipelines for collecting.

processing, and storing data from diverse social media sources and user interactions.

- Design of data warehouse.

- Implement rigorous data quality checks and validation processes to uphold the integrity.

accuracy, and reliability of social media data used by our AI models.

- Automate Extract, Transform, Load (ETL) processes to streamline data ingestion and transformation, reducing manual intervention and enhancing efficiency.

- Continuously monitor and optimize data pipelines to improve speed, reliability, and scalability, ensuring seamless operation of our AI Assistant.

- Collaborate closely with Data Scientists, ML Engineers, and cross-functional teams to understand data requirements and provide the necessary data infrastructure for model development and training.

- Enforce data governance practices, guaranteeing data privacy, security, and compliance with relevant regulations, including GDPR, in the context of social media data.

- Establish performance benchmarks and implement monitoring solutions to identify and address bottlenecks or anomalies in the data pipeline.

- Collaborate with data analysts and business teams to design interactive dashboards that enable data-driven decision-making.

- Develop and support data marts and dashboards that provide real-time insights into social media data.

- Stay updated with emerging data technologies, tools, and frameworks, evaluating their potential to improve data engineering processes.

Qualifications:

- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.

- Proven experience in data engineering, focusing on ETL processes, data pipeline development, and data quality assurance.

- Strong proficiency in programming languages such as Python, SQL and knowledge of data engineering libraries and frameworks.

- Experience with cloud-based data storage and processing solutions, such as AWS, Azure, or Google Cloud.

- Familiarity with DataOps principles and Agile methodologies.

- Excellent problem-solving skills and the ability to work collaboratively in a cross-functional team.

- Strong communication skills to convey technical concepts to non-technical stakeholders.

- Knowledge of data governance and data privacy regulations is a plus.