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Data Scientist

2 months ago


Ajax, Canada Colgate Full time

Established in 1806 as a small soap and candle business in New York City, Colgate-Palmolive is now a truly global company with products sold in over 200 countries and territories under such internationally recognized brand names as Colgate, Palmolive, Softsoap, Irish Spring, Protex, Sorriso, Kolynos, elmex, Tom's of Maine, Sanex, Ajax, Axion, Soupline, Haci Sakir, Suavitel, PCA SKIN, EltaMD, Filorga and Hello as well as Hill's Science Diet and Hill's Prescription Diet.

Colgate-Palmolive is a leading consumer products company that serves hundreds of millions of consumers worldwide with brands and products across four core businesses – Oral Care, Personal Care, Home Care and Pet Nutrition. We are committed to offering products that make lives healthier and more enjoyable, and programs that enrich communities around the world.

Every day millions of people trust our products to care for themselves and the ones they love. Our goal is to use our technology to create products that will continue to improve the quality of life for our consumers wherever they live.

A career at Colgate-Palmolive is an excellent opportunity if you seek a global experience, constant challenge, and development opportunities in an environment that respects work/life effectiveness.

Job Title: Data Scientist

Travel Required?: No Travel

Remote

Relocation Assistance Offered Within Country
# 161022 - Mumbai, Maharashtra, India

Who We Are
Colgate-Palmolive Company is a caring, innovative growth company that is reimagining a healthier future for all people, their pets and our planet. Focused on Oral Care, Personal Care, Home Care and Pet Nutrition, we sell our products in more than 200 countries and territories under brands such as Colgate, Palmolive, elmex, hello, meridol, Sorriso, Tom’s of Maine, EltaMD, Filorga, Irish Spring, PCA SKIN, Protex, Sanex, Softsoap, Speed Stick, Ajax, Axion, Fabuloso, Soupline and Suavitel, as well as Hill’s Pet Nutrition.

We are recognized for our leadership and innovation in promoting sustainability and community wellbeing, including our achievements in decreasing plastic waste and promoting recyclability, saving water, conserving natural resources and improving children’s oral health.

If you want to work for a company that lives by their values, then give your career a reason to smile and join our global team

What is the purpose of this role?
This role is expected to apply strong expertise in data science and machine learning through leading data collection & mining, data analysis, data visualizations, and predictive/prescriptive modeling efforts to build, test, and maintain analytics solutions which meet key business needs. This role will work with an analytics translator, other data scientists, and key business partners to define the business problem in a way that can be solved analytically.

What would be the responsibilities for this role?

  • Lead multifaceted analytic studies against large and small volumes of data for a variety of problems including projections, classifications, clustering, pattern analysis, simulations and more with junior data scientists.
  • Co-develop an analytics roadmap for the business domain to which you are assigned.
  • Interpret and analyze (structured and unstructured) data using exploratory statistical and mathematical techniques to identify trends, anomalies, and quantify business results.
  • Integrate data science work into user-facing applications and tools with data engineers, business leads, analysts and developers.
  • Build, deploy, maintain, and refresh end-to-end, repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products.
  • Identify and/or create new data as needed for use cases with limited data.
  • Work with data engineers to clean, massage, and organize data and to define data assets, eg, data models.
  • Lead the creation of analytical (e.g., code libraries & ML architecture) and data (e.g., external or partnership based data) assets.
  • Where needed, generate experiments on data using the scientific method, story-tell experimental results, and provide previously undiscovered solutions to data challenges.
  • Be the expert in the room on industry and field trends to push analytic builds towards best practices and state-of-art, as needed.
  • Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
  • Explain principles and approaches to business partners and senior management in a non-technical manner.

What does the ideal candidate profile look like?

  • Required
    • Academics: Bachelors Degree in Data Science, Mathematics, Computer Science, Engineering, Statistics, Econometrics or other related fields.
    • Minimum 6+ years’ experience in programming Languages - Python, R.
  • Preferred
    • Academics: PhD/Masters preferred.
    • Use case experience with demonstrated success in the sales analytics/ eCommerce domain.

What are the functional competencies required for this role?

  • SQL implementations (PostgreSQL, MySQL, Oracle, DB2).
  • Proven experience in translating business challenges into data pipelines & model framework.
  • Demonstrated expertise with supervised and unsupervised modeling including regressions, classifications, feature selection, clustering, decision tree/forest learning, SVM, ensembling & stacking, dimensionality reduction and more.
  • Fundamental understanding of Bayesian statistics and causal inference.
  • Strong proficiency in NLP (natural language processing).
  • Expertise with data visualization techniques & tools such as Plotly, matplotlib, ggplot2, etc, Shiny, Dash, Tableau, etc.
  • Demonstrated experience with large datasets and distributed computing (eg Spark).
  • Demonstrated experience with statistical tools or packages (eg SciKit) and ML frameworks (eg TensorFlow / PyTorch).
  • Proficiency or familiarity with relevant database/data engineering needs including:
    • Real-time data processing frameworks.
    • Metadata systems.
    • Data pipeline monitoring systems.
    • SQL implementations (PostgreSQL, MySQL, Oracle, DB2) ETL/ELT techniques, especially on cloud infrastructure (eg Google Cloud Platform).
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