At CPL Aromas we want to rely on powerfully insightful data to power our systems and solutions. We’re seeking an experienced data scientist to deliver that insight to us daily. Our ideal team member must have the mathematical and statistical expertise, but also natural curiosity and creative mind that’s not so easy to find.

 

 The Data Scientist will mine, interpret, and clean our data, we will rely on the DS to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the goal of realizing the data’s full potential. The Data Scientist will join a team IT Analysts but will “slice and dice” data be using agreed methods, creating new visions for the future.

 

  • Collaborate with perfumers, analytical and other key stake holders to develop an understanding of business requirements.
  • Research and devise innovative statistical models for data analysis
  • Communicate findings to all stakeholders
  • Enable smarter business processes—and implement analytics for meaningful insights
  • Keep current with technical and industry developments

  • Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products
  • Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries
  • Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables
  • Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy
  • Analyze data for trends and patterns, and Interpret data with a clear objective in mind
  • Implement analytical models into production by collaborating with software developers and machine learning engineers.
  • Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems.
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Extending company’s data with third party sources of information when needed
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Member of the Change Advisory Board (CAB) representing the integrity interest of BI and the associated User base.
  • Interact with business user groups and conduct regular Business Process improvement meetings leading to BI improvements/enhancements
  • Travel to CPL sites, adhering to group policies, any other duties as requested by the Manager/CIO

  • Master’s degree in stats, applied math, or related discipline
  • 2+ years of project management experience
  • Professional certifications
  • Data mining or extracting usable data from valuable data sources
  • Using machine learning tools to select features, create and optimize classifiers
  • Carrying out pre-processing of structured and unstructured data
  • Enhancing data collection procedures to include all relevant information for developing analytic systems
  • Processing, cleansing, and validating the integrity of data to be used for analysis
  • Analyzing large amounts of information to find patterns and solutions
  • Developing prediction systems and machine learning algorithms
  • Presenting results in a clear manner
  • Propose solutions and strategies to tackle business challenges
  • Collaborate with Business and IT teams
  • Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
  • Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies. 
  • Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests. 
  • Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques. 
  • Data Wrangling – proficiency in handling imperfections in data
  • Experience with Data Visualization Tools like Power BI, Tableau that help to visually encode data
  • Excellent Communication Skills – ability to present project details to a technical and non-technical audience.
  • Strong Software Engineering Background
  • Hands-on experience with data science tools
  • Problem-solving aptitude
  • Analytical mind and great business sense
  • Proven Experience as Data Analyst or Data Scientist
  • Nimble LEAN thinking ability to drive change that enables efficiencies and drives growth