{"id":4196631,"url":"https://alion.io/job/infovision-solutions-data-science-engineer","title":"Data Science Engineer","company":{"id":3808962,"name":"Infovision Solutions","domain":"infovision.com","url":"https://alion.io/company/infovision-solutions","size_band":null,"is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Copilot","optional":false},{"name":"Machine 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experience with libraries such as scikit-learn, pandas, NumPy, TensorFlow or PyTorch, and building modular, production-ready code.\n\nStrong SQL skills are required to extract, transform, and analyze large datasets from relational databases, supporting data preparation and model validation workflows.\n\nExperience using GitHub Copilot and AI-assisted coding tools to accelerate development cycles, improve code quality, and streamline repetitive engineering tasks is highly valued.\n\nCandidates must be comfortable working in a collaborative, agile environment in Bengaluru, partnering with data engineers, product managers, and business stakeholders to translate complex data problems into actionable ML solutions.\n\nYou will be expected to design and maintain robust data science workflows including model monitoring, retraining pipelines, and performance dashboards to ensure sustained model accuracy in production.\n\nA strong foundation in statistical modeling, experimentation frameworks such as A/B testing, and data storytelling to communicate insights clearly to both technical and non-technical audiences is required.\n\nRoles & Responsibilities:\nDesign, build, and deploy end-to-end machine learning models and pipelines using Python and modern ML frameworks, ensuring scalability and reliability in production environments.\nWrite complex SQL queries to extract and preprocess large volumes of structured data from enterprise databases, enabling high-quality feature engineering and exploratory data analysis.\nLeverage GitHub Copilot and other AI-assisted development tools to enhance coding productivity, enforce best practices, and reduce time-to-delivery for data science solutions.\nCollaborate with cross-functional teams including data engineering, software development, and business intelligence to integrate ML models into existing products and data platforms.\nMonitor deployed models for data drift, performance degradation, and bias, implementing automated retraining workflows and alerting mechanisms to maintain model health over time.\nConduct rigorous experimentation including hypothesis testing, A/B testing, and statistical validation to measure the real-world impact of ML-driven features and recommendations.\nDocument model architectures, data pipelines, experimental findings, and deployment processes to ensure reproducibility and knowledge sharing across the team.\nMentor junior data scientists and contribute to the team's technical growth by conducting code reviews, establishing coding standards, and promoting best practices in ML engineering.\nSkills\nMachine Learning, Python, 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