{"id":2859847,"url":"https://alion.io/job/weekday-director-applied-science","title":"Director Applied Science","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":88,"ghost_share":0,"stale_share":0.977,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":"head","employment_type":"full_time","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":{"min_usd":30000,"max_usd":73000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":99},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-19T15:54:56Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T02:43:40Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"'\n: - ( - )\nExperience: 16+ yrs\nLocation: Bengaluru\nWe are seeking an accomplished Director of Applied Science to lead advanced machine learning and artificial intelligence initiatives that drive innovation, improve business outcomes, and expand the capabilities of data-driven products and services. The ideal candidate will combine deep technical expertise, strategic leadership, and a strong track record of delivering production-grade AI/ML solutions.\nThis role requires an experienced leader who can define the applied science vision, guide research and experimentation, and translate scientific advancements into scalable business applications. You will lead applied scientists and machine learning engineers, establish technical standards, and collaborate with Product, Engineering, and Data teams to deliver measurable business impact.\nRequirements\nKey Responsibilities\nLead and develop a team of applied scientists and machine learning engineers building advanced models, algorithms, and AI-powered solutions.\nDefine the technical vision, research strategy, and roadmap for applied science initiatives in alignment with business priorities.\nIdentify opportunities to apply machine learning, deep learning, and advanced analytics to complex business problems.\nOversee experimentation, model development, evaluation, validation, and deployment into production environments.\nGuide the development of supervised, unsupervised, and deep learning solutions for real-world applications.\nPartner with Product, Engineering, and Data teams to integrate ML models into scalable, reliable, and high-performance systems.\nEstablish best practices for scientific experimentation, statistical validation, reproducibility, model monitoring, and continuous improvement.\nChampion responsible AI principles, including model transparency, fairness, reliability, and appropriate risk management.\nEvaluate emerging research, algorithms, and technologies to identify opportunities for innovation and competitive advantage.\nEnsure projects are delivered within agreed timelines and scope while maintaining technical quality and business relevance.\nMonitor project progress, manage technical risks, remove blockers, and prioritise resources across multiple initiatives.\nMentor scientists and engineering leaders, strengthen technical capabilities, and foster a culture of innovation and continuous learning.\nDefine success metrics and evaluate the business impact of applied science initiatives.\nRepresent the applied science function in executive discussions, strategic planning, and technology roadmap decisions.\nWhat Makes You a Great Fit\n16+ years of experience in applied science, machine learning, artificial intelligence, or related technical fields.\nAt least 3 years of experience in a management or technical leadership role, leading scientific or ML engineering teams.\nA PhD or Master's degree in Machine Learning, Computer Science, Statistics, or a related discipline.\nProven experience building, deploying, and scaling machine learning models in production systems.\nDeep understanding of supervised learning, unsupervised learning, deep learning, and advanced modelling techniques.\nStrong programming skills in Python and hands-on proficiency with frameworks such as PyTorch or TensorFlow.\nExperience leading research-driven initiatives and translating scientific findings into practical product or business solutions.\nStrong understanding of model evaluation, experimentation, statistical validation, and production ML lifecycle practices.\nDemonstrated ability to define technical strategy, manage complex projects, and deliver measurable business outcomes.\nExcellent people leadership, mentoring, and team development capabilities.\nStrong communication and stakeholder-management skills, with the ability to engage technical teams and executive leadership.\nA strategic, analytical, and innovation-oriented mindset with a commitment to scientific rigour and responsible AI.","description_format":"text","description_chars":3969,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous 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