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Principal Data Scientist

Sigmoid
Posted 11 days ago, valid for 10 days
Location

Newark, NJ 07188, US

Salary

$150,000 - $180,000 per year

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Contract type

Full Time

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Sonic Summary

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  • The Principal Data Scientist role focuses on leading commercial analytics and RGM engagements while collaborating with senior client stakeholders.
  • Candidates should possess 8-12 years of overall experience, including 3+ years in consulting or client-facing analytics roles, specifically in CPG or adjacent environments.
  • The position requires strong expertise in machine learning, statistics, and proficiency in SQL, Python, and PySpark, along with experience in cloud platforms like Snowflake and AWS.
  • Key responsibilities include developing analytics models, leading client workshops, and maintaining relationships to ensure account success.
  • The salary for this position is competitive and commensurate with experience.

Role: Principal Data Scientist - Commercial Analytics

Title: Senior Lead, Principal Data Scientist / Associate Director - Data Science

Location: NY / NJ (USA)

Summary:  The role is expected to serve as the primary client-facing data science lead for commercial analytics and RGM engagements. In this role, you will partner with senior client stakeholders, translate business challenges into data science solutions, review and guide offshore deliverables, and ensure delivery of high-quality outcomes. You will combine hands-on modeling expertise with client leadership, solution ownership, and team guidance to drive measurable business impact Provide clear guidelines for offshore development teams & own outcomes. You will nurture key client relationships to ensure client account success

Desired Experience : 

  • 8–12 years of overall experience.
  • 3+ years in consulting or client-facing analytics roles.
  • 3+ years of experience in CPG or adjacent commercial analytics environments.
  • Proven experience engaging with senior stakeholders and leading client conversations.
  • Strong track record in data science, statistics, and machine learning

 

Role & Responsibilities :

  • Develop and refine analytics & ML models and tools (e.g., Price Elasticity, iPPA diagnostics, Portfolio Simulators, TPO, TPM etc.) to support strategic RGM decisions
  • Employ your analytical skills to decipher large datasets, and identify opportunities to enhance existing solutions, as well as develop new ones as scalable proof-of-concepts (PoC).
  • Work closely with cross-functional teams, including data scientists, data engineers and product managers and business experts to ensure the smooth development of RGM models and translate outcomes to business stakeholders
  • Collaborate extensively with business stakeholders to gather requirements, deeply understand challenges and identify opportunities.
  • Leading client workshops where broad vision and ambiguous business problems are articulated to be solved through data analytics and AI
  • Independently liaise with customers and convincingly present solutions in an unstructured and ever-changing client environment. Be able to independently question the customer, when required.
  • Perform a role that involves a combination of hands-on contribution and customer engagement
  • Contribute to organization building through training, mentoring, and developing repeatable analytic approaches


Primary Skills (Mandatory)

  • Strong foundation in ML and statistical concepts.
  • Proficiency in SQL, Python, and PySpark.
  • Experience with Snowflake, BigQuery, Azure, AWS, or Databricks.
  • Experience with CPG data and commercial analytics, including pricing, promotion, mix, e-commerce, or customer analytics.
  • Ability to convert rigorous analysis into strategic recommendations.
  • Strong project management, communication, and team leadership skills
  • Strong problem-solving skills and a creative mindset for disrupting how RGM analytics is conducted today. Be at the forefront of innovations in commercial analytics space

 

 Secondary Skills (Good to have):

  • Exposure to supply chain analytics, manufacturing analytics, or e-commerce analytics.
  • Data engineering / MLOps experience.
  • Dashboarding experience with Power BI or Tableau
  • Exposure to Agentic AI / LLMs or any other Gen AI capabilities



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