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Senior Data Scientist

Poland / Remote / Ukraine

About Akvelon

🌎Akvelon is an American company with offices in Seattle, Mexico, Ukraine, Poland, and Serbia. Our company is an official vendor of Microsoft and Google. Our clients also include Amazon, Evernote, Intel, HP, Reddit, Pinterest, AT&T, T-Mobile, Starbucks, and LinkedIn. To work with Akvelon means to be connected with the best and brightest engineering teams from around the globe and working with an actual technology stack building Enterprise, CRM, LOB, Cloud, AI and Machine Learning, Cross-Platform, Mobile, and other types of applications customized to client’s needs and processes.

As a Senior Data Scientist you will be responsible for leveraging advanced analytics and data science techniques to support Actuarial and Forecasting Systems within the organization. You will play a crucial role in developing predictive models, analyzing complex data sets,and providing insights to drive strategic decision-making in the actuarial and forecasting domains.

Requirements:

​• Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial
sciences, science and engineering, or related field OR 4 years of relevant experience;
• Experience in predictive analytics or data analysis OR Advanced Degree (e.g., Master’s, PhD) in
quantitative discipline along with 4 years of experience in predictive analytics or data analysis;
• Proficiency in training and validating various advanced analytics models;
• Proficiency in at least one dynamic scripted language (e.g., Python, R) for statistical analysis and
AI/ML model development;
• Demonstrated ability to write well-documented and easily understandable code;
• Strong skills in querying and preprocessing data from structured and unstructured databases
using SQL, HQL, NoSQL, etc;
• Experience working with various types of data files including delimited numeric data, JSON/XML
files, text documents, images, etc;
• Skilled in performing ad-hoc analytics using various statistical methods;
• Ability to understand and communicate regulatory implications related to modeling efforts;
• Advanced knowledge of classical supervised modeling techniques like regression, SVMs, decision
trees, etc;
• Advanced knowledge of unsupervised modeling techniques such as clustering algorithms;
• Experience in guiding and mentoring junior technical staff;
• Ability to effectively communicate analytical results to non-technical stakeholders;
• Previous experience as a Data Scientist in the financial industry, particularly in actuarial or
forecasting domains;
• Strong understanding of statistical modeling, time series analysis, and predictive analytics;
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS,
Azure);
• Excellent problem-solving abilities and aptitude for both independent and team-based work;
• Strong communication skills for presenting complex findings to non-technical audience.

Responsibilities:

• Develop and implement advanced machine learning algorithms for actuarial modeling and
forecasting;
• Analyze large datasets to extract meaningful patterns and insights for improving forecasting
accuracy;
• Collaborate with cross-functional teams to understand business requirements and translate
them into data science solutions;
• Build and maintain predictive models to support actuarial calculations and risk assessments;
• Evaluate model performance, conduct model validation, and ensure compliance with regulatory
standards;
• Communicate findings and recommendations to stakeholders in a clear and concise manner;
• Gathers, interprets, and manipulates structured and unstructured data for advanced analytical
solutions;
• Develops scalable, automated solutions using machine learning, simulation, and optimization for
business insights;
• Selects appropriate modeling techniques considering data limitations, application, and business
needs;
• Deploys models within the Model Development Control (MDC) and Model Risk Management
(MRM) framework;
• Composes technical documents for knowledge persistence, risk management, and technical
review;
• Proposes analytical projects to enhance business value, prioritizing with leaders;
• Builds a library of production-quality algorithms to ensure transparent model development;
• Translates complex business requests into specific analytical questions and communicates
outcomes effectively;
• Manages project milestones, risks, and impediments, escalating issues if needed;
• Develops best practices for deploying production-ready analytical assets in line with standards;
• Maintains expertise in cutting-edge techniques, actively seeking new learning opportunities;
• Participates in internal communities driving data science technologies and culture
transformation;
• Ensures effective identification, measurement, monitoring, and control of risks in business
activities.

Working Conditions and Benefits:

🔸Paid vacation and sick leave (without requiring a sickness list);
🔸Health insurance;
🔸Official state holidays — 11 days considered public holidays;
🔸Opportunities for professional growth through challenging projects and the possibility to switch roles, master new technologies, and improve skills with company support;
🔸Flexible working schedule: 8 hours per day, 40 hours per week, with 2-3 hours of overlap with PST;
🔸Personal Career Development Plan (CDP);
🔸Employee support program (Discounts, Care, Health, Legal compensation);
🔸Paid external training, conferences, and professional certification aligned with the company’s business goals;
🔸Internal workshops and seminars;
🔸Corporate library (paper and e-books) and internal English classes.

If you are a motivated and talented Data Scientist seeking a challenging opportunity with a global technology company, this position is perfect for you.

Anzhelika Mumriak

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