Need & _Senior Manager Data Science_Chevy Chase, MD(Day 1 Onsite)

  • Chevy Chase, MD, MD
  • Posted 11 days ago | Updated 1 day ago

Overview

On Site
$DOE
Full Time
Accepts corp to corp applications
Contract - W2
Contract - Independent

Skills

Sales
SQL
Python
Database design
Data Science
ml
Project Lead
Stakeholders
data architecture
data pipelines
machine learning
algorithms
AI
Team management

Job Details

Position:Senior Data Science Manager
Location:Chevy Chase, MD(Day 1 Onsite)
Duration:12 months
Experience: 15+ Years
Job Descrpition:
As a Senior Manager of Data Science, you will be responsible for:
  • Collaborate with and provide strategic guidance to stakeholders across sales, FP&A, and customer care, ensuring data-driven insights contribute to the overall success of revenue initiatives.
  • Lead a team of Data Scientists both strategically and drive the development and the implementation of machine learning models to solve core business problems, such as pricing optimization, elasticity modeling, customer churn, lead scoring, lifetime value, and recommender systems.
  • Lead customer segmentation efforts to generate insights that can inform our sales and acquisition strategy in a subscription-based plan scenario.
  • Spearhead end-to-end projects, from initial ideation and business alignment to measurement and deployment of insights, ensuring a strategic approach and alignment with broader business objectives.
  • Play a pivotal role in assisting teams in defining KPIs, setting strategic goals, and designing and analyzing A/B testing for data-driven decision-making, emphasizing a strategic and impactful contribution.
  • Oversee the development and maintenance of reports and data products for the organization, utilizing various tools such as Streamlit, Shiny, Looker, or Qlik sense, to provide actionable insights that contribute to data-informed decisions.
  • Effectively communicate, collaborate, and present results to stakeholders within Client, driving the adoption of data-informed decision-making processes throughout the organization.
  • Explore and implement novel methodologies to analyze data for continuous improvement, staying abreast of industry best practices and emerging trends in data science.
  • Mentor and guide team members in analytic and statistical best practices, fostering a collaborative and learning-oriented environment within the Data Science team.
Must Have:
  • Advanced academic background with a master's or Ph.D. degree in Statistics, Mathematics, Data Science, Engineering, or a related field.
  • Proven experience in leading and managing data science teams, with at least 3 years of experience in a leadership role.
  • Exceptional expertise and demonstrated thought leadership in metrics and models relevant to Retention and Pricing Strategy, emphasizing strategic contributions to organizational goals.
  • Mastery of applied statistics, showcasing a deep understanding of hypothesis testing and forecasting with hands-on experience in building ML algorithms to uncover actionable insights on retention and pricing strategy and segmentation.
  • Proficiency in advanced SQL and Python programming, with the ability to develop and implement sophisticated data manipulation and analysis techniques.
  • A high-level understanding of data architecture, data pipelines, and database design, demonstrating the ability to guide and optimize these processes with Data Platform partners.
  • Proficiency in at least one advanced visualization tool, coupled with a strategic approach to data visualization that enhances decision-making processes.
  • Excellent communication skills, both written and verbal, with the ability to articulate complex concepts to diverse audiences, including non-technical stakeholders.
  • A strategic mindset with the ability to translate complex business problems into innovative analytics opportunities and solutions.
  • A collaborative leadership style that fosters a culture of data-driven decision-making across the organization.
  • An innovative spirit, constantly exploring and implementing new ideas and approaches to address challenging problems.