{"id":2906675,"url":"https://alion.io/job/lufthansa-technik-services-india-data-science-team-manager-aiml","title":"Data Science Team Manager - AI/ML","company":{"id":3800300,"name":"Lufthansa Technik Services India","domain":"lht-services-india.com","url":"https://alion.io/company/lufthansa-technik-services-india","size_band":null,"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":"staff","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":{"min_usd":31000,"max_usd":58000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Hadoop","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLP","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scala","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-09-18T12:17:29Z","employer_posted_date":null,"last_verified_at":"2026-09-18T12:17:29Z","board_verified":false,"closed_at":null,"days_open":42,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":42},"description":"I. Detailed Role Description:\n\nWe are looking for a highly skilled and visionary Data Science Team Manager (AI/ML) to lead a team of data scientists and machine learning engineers. This role is responsible for driving AI/ML initiatives that solve complex business problems, building scalable models and ensuring successful deployment into production systems. The ideal candidate combines hands-on technical expertise with strong leadership, business acumen and the ability to align data science strategy with organizational goals.\n\nII. Roles and Responsibilities:\n\nStrategic Leadership & Vision:\n\n- Develop and execute a comprehensive data strategy that integrates analytics and data science to drive business outcomes, such as revenue growth, operational efficiency and customer satisfaction.\n\n- Translate business objectives into data-driven initiatives that deliver measurable value across departments.\n\n- Lead Digital transformation for LTSI organization with strategic forecast on LHT vision 2030.\n\n- Define team goals, set priorities and allocate resources effectively.\n\n- Foster a culture of innovation, collaboration and continuous learning.\n\n- Provide technical guidance and ensure best practices in AI/ML development.\n\n- Initiate Hackathons and Capability Roadshows to find solutions to address LH's global challenges.\n\nTeam Leadership & Development:\n\n- Lead, mentor and manage teams of 20+ Data Analysts, Data Scientists, AI/MLOps professionals, Vision computing experts and AI platform engineers, fostering a culture of innovation, collaboration and technical excellence.\n\n- Foster a collaborative and innovative culture that encourages experimentation, learning, and continuous improvement.\n\nAI/ML Strategy & Execution:\n\n- Take complete responsibility of development and deployment of advanced machine learning models, predictive analytics and AI solutions for applications like forecasting, customer segmentation or process automation.\n\n- Support organization with defining & executing the AI/ML strategy aligned with the company's business goals.\n\n- Set up an SOP for shared leadership between Germany & BLR in identifying POC's that can be productionized.\n\n- Stay current with emerging trends in AI/ML and guide the adoption of cutting-edge techniques.\n\n- Oversee the end-to-end lifecycle of ML projects: problem framing, data preparation, model design, training, validation, deployment and monitoring.\n\n- Ensure models are accurate, explainable, scalable and robust for production environments.\n\n- Drive experimentation and adoption of cutting-edge AI/ML techniques (e.g., deep learning, NLP, computer vision, generative AI).\n\n- Drive experimentation culture to evaluate and benchmark algorithms and solutions.\n\nBusiness Development:\n\n- Identify and capitalize on growth opportunities using data-driven insights to shape market strategies, pitch solutions to clients and partners and secure new business.\n\n- Recognize potential roles that can be transitioned from high-cost locations (HAM, MIA) to lower-cost locations (India).\n\n- Establish a potential IT team, including full stack development and technical support roles (L2, L3).\n\n- Position LTSI as a Center of Competence for Advanced Data Analytics and AI Solutions.\n\nCross-Functional Collaboration & Business Impact:\n\n- Collaborate with C-suite executives and department heads to ensure that analytics and data science initiatives align with organizational goals, promoting data-driven decision-making throughout the company.\n\n- Identify potential digitization and automation opportunities with over 20 teams in LTSI and implement strategies to enhance quality and efficiency.\n\n- Work with LTSI teams to develop digital skills and prepare a future-ready workforce.\n\n- Initiate Digital Literacy programs for tailored for all LTSI employees.\n\n- Partner with product, engineering and business stakeholders to identify opportunities for AI/ML applications.\n\nData Infrastructure & Governance:\n\n- Collaborate with global IT and engineering teams to ensure robust, scalable data pipelines, cloud infrastructure (AWS, Azure, GCP), and compliance with data governance and privacy regulations.\n\n- Setup digital infrastructure to enable LTSI support functions to operate efficiently.\n\n- Ensure data quality, integrity, and security while adhering to compliance standards.\n\n- Collaborate with data engineering teams to build and optimize data pipelines.\n\n- Ensure data governance ambassadors are in place.\n\n- Promote best practices in MLOps, model monitoring and continuous improvement.\n\nPerformance Measurement:\n\n- Define KPIs and metrics to evaluate the impact of analytics and data science initiatives on business outcomes.\n\n- Set annual cost saving targets and ensure these targets are met by implementing automation, strategic projects.\n\n- Ensure the agreed upon KPI's and objectives are successfully achieved.\n\nStakeholder Communication:\n\n- Develop and distribute project charters, and clearly outline milestones.\n\n- Optimize the utilization of budgeted FTEs.\n\n- Communicate complex data insights, model outcomes, and strategic recommendations to non-technical stakeholders, including board members, clients, or partners.\n\nInnovation & Trends:\n\n- Establish an innovation hub at LTSI to generate viable ideas and secure funding for their implementation.\n\n- Stay ahead of industry trends in analytics, AI, and machine learning, integrating cutting-edge methodologies to maintain a competitive edge.\n\nKey Skills:\n\n- Expertise in analytics tools (SQL, Tableau, Power BI) and data science frameworks (Python, R or Scala, TensorFlow, PyTorch, Scikit-learn, XGBoost, etc).\n\n- Solid understanding of deep learning, NLP, computer vision, recommender systems or generative AI.\n\n- Knowledge of big data technologies (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).\n\n- Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).\n\n- Experience with statistical analysis, machine learning and predictive modeling.\n\n- Strong business acumen with experience in strategic planning and business development.\n\n- Proven leadership and team management skills, with the ability to inspire and align diverse teams.\n\n- Exceptional communication and presentation skills to influence stakeholders and articulate data-driven strategies.\n\n- Knowledge of data engineering and data governance principles.\n\n- Ability to bridge technical and business domains, translating complex data concepts into actionable strategies.\n\nQualifications:\n\n- Master's/PhD in Data Science, Statistics, Computer Science, Business Administration or a related field.\n\n- 12+ years of experience in analytics and/or data science/ML roles, with 4+ years in a senior leadership role overseeing both functions.\n\n- Proven track record of delivering AI/ML solutions in production.\n\n- Proven track record of driving business impact through data initiatives and business development efforts.\n\n- Experience in client-facing roles or strategic partnerships is a plus.\n\nSkills\nData Science, Machine Learning, Python, MLOps, Deep Learning, NLP, Computer Vision, Generative AI, Big Data, Artificial 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