Data Scientist

Job title: Data Scientist

Company: Invesco

Job description: Job Purpose (Job Summary):

The Data Scientist is an important role in the Invesco’s Insights & Analytics organization working across Invesco’s retail and institutional businesses in the Americas. Reporting to the Lead Modeler, the role will help optimize the roadmap for client data and delivery of client intelligence. The end goal is to increase net sales of Invesco products through targeted sales and marketing activities based on data driven understanding of our clients.

The person will:

  • Drive a hypothesis-driven approach to create client insights
  • Build advanced predictive models to help optimize segmentation and targeting
  • Work closely with colleagues in India and North America Distribution to ensure that insights and tools are leveraged to improve sales and marketing ROI
  • Leverage learnings from current projects to define requirements for future analytical roadmap
  • Demonstrate strong business acumen (e.g., comfortable dealing with ambiguity, demonstrates strong business judgment, outcome-oriented with demonstrated drive for results), and communication (demonstrated ability to synthesize insights, strong written/oral communications)

The Department: Insight and Analytics

Insight and Analytics is responsible for increasing data driven decision making at Invesco. The group works mostly with the Americas Distribution and Marketing teams to help increase net sales through a better understanding of our clients (financial advisors). It works like a small startup within the organization, with a clear focus on improving effectiveness and efficiency through end-to-end management of data, analytics, visualization and in-field implementation. While the team is not new, there is a distinct focus on restructuring the talent through training and recruiting as well as redefining the vision and engagement model with the rest of the organization. In short, it’s an exciting place to be at for self-starters who want to set and own their paths forward.

Key Responsibilities / Duties:


  • Maintain the code and capability environment required to evolve data-driven, analytical capabilities with the end goal of understanding customer behavior and competitive dynamics
  • Collaborate with customer analytics and digital analytics experts to define and develop differentiating go to market analytics features and frameworks
  • Work with ambiguity (e.g. imperfect data, loosely defined concepts, ideas, or goals) and translating these into more tangible outputs
  • Articulate and lead data sciences initiatives, using both directly managed resources and dedicated resources available in an agile project environment
  • Provide ongoing monitoring of performance of decision systems and statistic models
  • Define metrics on business outcomes (particularly those related to new capabilities) that are clear, accurate, relevant, logical and honest
  • Exhibit strong problem-solving skills and the ability to work well in a team environment, prioritize work, analyze interdependencies and deliver against deadlines

Data Management:

  • Partner with the Data team to optimize the cloud based aws / redshift environment in order to support an always on data sciences capability
  • Help specify business and technical requirements for data ingestion, verification, scheduling, etc. across first party, second party and third party data
  • Help build out the data engineering and feature engineering capabilities required to support customer centric analytics and visualization
  • Collaborate with business subject matter experts and IT teams to make strategic recommendations on data collection, integration and retention

Work Experience / Knowledge:

  • 5+ years of hands-on experience developing and applying predictive models and other advanced statistical approaches in a corporate or consulting setting, preferable in a B to B or customer centric environment (extensive experience with financial transaction data is a plus)
  • 2+ years of analytical project management experience
  • Strong technical competence, with ability to teach / train associates:
  • Deep practical expertise and theoretical understanding of Classification (SVM, nearest neighbors, random forest, etc.), Regression (linear, nonlinear, ridge, lasso, etc.), Clustering (k-means, spectral, etc.), Dimensionality Reduction (PCA, ICA, etc), Model selection (grid search, cross validation, etc), Data Cleansing (pre-processing, feature extraction)
  • Proficiency in statistical data analysis and data mining packages
  • Advanced knowledge of data management tools
  • Advanced programming skills
  • Comfortable in using data visualization tools

Skills / Competencies/attributes:

  • Intellectual curiosity, along with excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions
  • Ability to effectively balance implementation of highly technical models in a sales environment
  • Superior communication and influencing skills
  • Ability to work in agile, test & learn, and iterative environment
  • Stong organizational skills and detail orientation

Formal Education:

  • Undergraduate or advanced degree in a quantitative discipline (i.e. Statistics, Mathematics, Econometrics, Operations Research, Computer Science) with focus on data sciences techniques
  • Strong academic qualifications, including advanced understanding/coursework in database management and math (Linear, Algebra, Calculus)

Disclaimer: The above information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job. Incumbents may be required to perform other duties as deemed appropriate by the supervisor from time to time.

Expected salary:

Location: Hyderabad, Telangana – Andhra Pradesh

Job date: Fri, 08 Jan 2021 04:52:00 GMT

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