{"id":3454106,"url":"https://alion.io/job/proxet-senior-data-scientist","title":"Senior Data Scientist","company":{"id":3807134,"name":"Proxet","domain":"proxet.com","url":"https://alion.io/company/proxet-2","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Ukraine"],"countries":["UA"],"hiring_countries":["UA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":62000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Claude Code","optional":false},{"name":"Databricks","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-26T02:50:58Z","employer_posted_date":null,"last_verified_at":"2026-10-26T02:50:58Z","board_verified":false,"closed_at":null,"days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"description":"We are looking for a highly skilled Senior Data Scientist to join our team. As a Senior Data Scientist, you will be responsible for designing and implementing advanced data models, analyzing complex business problems, and developing solutions that help optimize sales, marketing, pricing, and overall commercial performance in a leading American publishing house.\n\nThe role will contribute to the transition from primarily descriptive analytics toward more advanced, data-driven decision making.\n\nSkills & Experience\n\nBachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or a related field;\n\n5+ years of experience in data science roles;\n\nStrong experience applying data science and machine learning to business problems, ideally in areas such as sales, marketing, customer behavior, demand forecasting, or pricing optimization;\n\nProficient in Python and SQL for data analysis, scripting, and machine learning;\n\nProficient in using agentic coding tools like Claude Code, Codex, Cursor\n\nExperience with SciKit-learn, Pytorch, and similar machine learning frameworks for building and deploying machine learning models;\n\nExperience working with modern data warehouses/lakehouses like Snowflake, Databricks, BigQuery, Redshift\n\nStrong analytical and problem-solving skills, with the ability to translate ambiguous business problems into data-driven solutions;\n\nAbility to work independently and collaborate with business and technical stakeholders;\n\nFluent in English and excellent communication skills.\nNice to have: \n\nStrong background in data science, with extensive experience in leveraging advanced analytics and machine learning to drive data-driven business decisions.\n\nResponsibilities\n\nDesign, develop, and implement advanced data models and machine learning algorithms to solve complex problems in the publishing domain, like author discovery;\n\nAnalyze sales, marketing, customer, product, and pricing data to identify opportunities and support business decisions;\n\nDevelop data-driven approaches to areas such as demand forecasting, customer behavior, sales optimization, marketing effectiveness, and pricing;\n\nWork with business stakeholders to understand broad or ambiguous business challenges and translate them into analytical and machine learning solutions;\n\nCollaborate with cross-functional teams to understand data requirements and deliver actionable insights and recommendations;\n\nBuild and maintain scalable data pipelines using technologies such as Snowflake, and DBT;\n\nLeverage Python and SQL for data analysis, model development, experimentation, and automation;\n\nUtilize SciKit-learn, Pytorch and similar frameworks for developing and deploying machine learning models;\n\nHelp evolve the organization from descriptive analytics toward predictive and prescriptive analytics and data-driven decision making;\n\nStay current with emerging trends and technologies in data science and machine 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