Lead Data Scientist

Lead Data Scientist

10-13 years
Not Specified

Job Description

Join a team recognized for leadership, innovation and diversity

Lead Data Scientist
The ISC Analytics team, is responsible for identifying data and empowering business users with actionable insights to improve Supply Chain operational performance and process efficiencies. The skills mix of this team is a blend of an exhaustive knowledge of supply chain concepts, data analysis, data engineering, data science and diverse problem-solving capabilities.
The team uses an extensive list of analytics tools including but not limited to Snowflake, Dremio, Data Bricks, SQL, Alteryx, Tableau, Python and SAP HANA platforms to perform advanced analysis on key metrics and initiatives.
In this role, you will be engaging with Supply Chain Leaders/ Decision makers across HON to define & deliver on supply chain Analytics solutions that will increase efficiencies/reduce costs/drive Supply Chain transformation.
The Lead Data Scientist of the ISC Analytics team would support a range of data analysis initiatives in Supply chain organization through analysis, process improvements & project management. He/she is responsible to define the Data sourcing strategy and works with partners to procure data for solving the problem statements from leadership. Lead Data Scientist works as an individual contributor, facilitates KPI Performance improvements and optimization across supply chain. Act as a mentor to other team members in Data Science area.
  • Interact with business groups to understand critical business problems
  • Identify and drive broad research directions using AI/ML
  • Manage and mentor junior data scientists to create cutting edge data-driven systems and technologies that can considerably impact the business outcomes.
  • Be a scientific leader who can also enable strong presence in scientific community via research publications, tutorials, workshops, and collaborate with research institutions with renowned researchers in the field of interest
  • Contribute to the future vision and innovation needed to the growth of the organization
  • Use of cutting-edge Analytics techniques for building advanced prediction and recommendation systems, knowledge mining, insight generation, and business automation
  • Understand business challenges and goals to formulate the approach for data analysis and model creation that will support business decision making
  • Research on innovative technologies to come up with novel data mining, modelling/segmentation approaches required to solve unique and complex business problems, as well as create publications and patents from them
  • Interpret, document and present/communicate analytical results to multiple business disciplines, providing conclusions and recommendations based on customer-centric data
  • Coach & mentor Data Scientists

  • Strong intuition for data and keen aptitude on large scale data analysis.
  • Software engineering fundamentals, including coding, problem solving and data analysis skills.
  • Engage with external ecosystem (academia, technology leaders, open source etc.) to develop the skills and technology portfolio of the team.
  • Excellent problem-solving ability and results oriented focus. Ability to translate analysis and insights into actionable recommendations.
  • Understand ambiguous issues / scenarios - able to distil learning and simplify
  • Ability in self-learning, entering new domain, managing through uncertainty in an innovative team environment.
  • Excellent analytical skills with demonstrated ability to query, analyses, explain and draw logical conclusions from operational & financial data and present findings in a simple manner
  • Strong financial acumen with the ability to interpret financial data
  • Innovative, creative, and proactive.
  • Ability to communicate complex models and analysis in a clear and precise manner.
  • Highly driven, energetic, flexible, resourceful & ability to multitask.
  • Strong influencing skills, including demonstrated ability to influence and drive results at all levels of the organization
  • Team Player, open to feedback, and flexible & adaptable to changing needs.

Education: BE/ B Tech in any Engg. discipline + MS/MBA in Business Analytics,
Supply chain Operations, Industrial Engineering, or any related field. MBA and CPIM is a plus
Certifications in Business Analytics
Experience: 10+ years of Proven Data Analysis & Simulation Experience.
4-5 Years (PHD qualification) is mandatory
  • Applied experience: 8+ years of ML and/or AI production level experience.
  • 10+ years hands-on experience in algorithms and implementation of analytics solutions in predictive analytics.
  • Experience with building data analytics models via supervised and unsupervised machine learning and deep learning, NLP, Computer vision, reinforcement learning, statistical analysis, and predictive modelling techniques.
  • 5+ years of work experience in Advanced SQL and relational databases.
  • Strong analytical and quantitative problem-solving ability.
  • 3+ years of work experience with data visualization tools using Qlik Sense, Power BI, Tableau
  • 3+ years of work experience with SAP or other ERP's.
  • Demonstrated ability in building AI/ML based solutions using a variety of frameworks such as Python, R, H2O, Keras, TensorFlow, Spark ML etc.
  • Project Management skills - Ability to manage a project, report out on action status, and provide clear verbal and written status.

About Honeywell

Honeywell International Inc. is an American publicly traded, multinational conglomerate corporation headquartered in Charlotte, North Carolina. It primarily operates in four areas of business: aerospace, building technologies, performance materials and technologies (PMT), and safety and productivity solutions (SPS).
Honeywell is a Fortune 100 company, ranked 94th in 2021. The corporation in 2020 had a global workforce of approximately 103,000 employees, down from 113,000 in 2019. The current chairman and chief executive officer (CEO) is Darius Adamczyk.
The corporation's current name, Honeywell International Inc., is a product of the merger of Honeywell Inc. and AlliedSignal in 1999. The corporation headquarters were consolidated with AlliedSignal's headquarters in Morristown, New Jersey; however, the combined company chose the name 'Honeywell' because of the considerable brand recognition.[8] Honeywell was a component of the Dow Jones Industrial Average index from 1999 to 2008. Prior to 1999, its corporate predecessors were included dating back to 1925, including early entrants in the computing and thermostat industries.

Job Source : careers.honeywell.com

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