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Data Scientist

  • Job
    Full-time
    Mid, Senior & Expert Level
  • Science
    Data
  • Hyderabad, +1

AI generated summary

  • You need a quantitative degree, 3+ years in quant research and portfolio optimization, ML skills, Python proficiency, basic data engineering, Azure experience, and familiarity with Snowflake and ETL tools.
  • You will design and implement ML solutions, analyze market signals, build forecasting models, automate processes, communicate insights to teams, and lead research projects with defined objectives.

Requirements

  • B.Tech/M.Tech/MS/Ph.D. in a quantitative discipline (math, statistics, computer science, engineering, finance)
  • Minimum of 3 years of experience in quantitative research and portfolio optimization.
  • Mastery of probability, statistical inference, time series forecasting, and machine learning (ML). You can differentiate signal from noise and avoid common pitfalls of applying ML to noisy datasets.
  • Proficient in python and common data science libraries (e.g. pandas, numpy, scikit-learn)
  • Proficient in the basics of data engineering. You can load data into a warehouse, design and build simple database models, and write moderately complex SQL queries to power your research.
  • Experience in quant research applied to financial markets and investing. Real estate experience a plus, but not required.
  • You have built end-to-end systems (data, models, UI) in a multi-asset context.
  • Comfortable with data science project/product management.
  • Proficient with cloud computing in Azure, working with virtual machines, serverless functions, cloud storage, data pipelines, etc.
  • Experience with Snowflake and ETL tools like Matillion & Azure Data Factory.

Responsibilities

  • Lead the design & build of a quantitative research system supporting investment decisions for commercial real estate portfolios allocating billions of dollars in AUM
  • Design, develop and implement ML/AI solutions for real estate markets.
  • Find the needle in the haystack - identify the signals that are most descriptive and predictive of market performance.
  • Train time series forecasting and cross-sectional ranking models across hundreds of geographies and property types. Use these data-driven views to construct risk-efficient model portfolios.
  • Help the team build automated processes to support the quant research system using best practices in data engineering, cloud computing, and software development.
  • Communicate complex quantitative ideas & insights to investment teams (analysts, PMs, underwriters, etc.) to improve adoption of solutions delivered by the data science team.
  • Scope, lead, and execute research projects with clearly defined deliverables and timelines. Provide input to leadership to support development of a long-term roadmap.

FAQs

What primary responsibilities does the Data Scientist have at Clarion Partners?

The Data Scientist is responsible for leading the design and build of a quantitative research system, implementing ML/AI solutions for real estate markets, identifying predictive signals for market performance, training forecasting models, automating processes for the quant research system, communicating insights to investment teams, and executing research projects with defined deliverables and timelines.

What qualifications are required for this Data Scientist position?

Candidates should have a B.Tech/M.Tech/MS/Ph.D. in a quantitative discipline, a minimum of 3 years of experience in quantitative research and portfolio optimization, mastery of probability, statistical inference, machine learning, proficiency in Python and data science libraries, as well as basic data engineering skills.

Is experience in real estate necessary for this role?

While experience in real estate is a plus, it is not required. Experience in quantitative research applied to financial markets and investing is essential.

Where is the Data Scientist position based?

The position can be based out of Hyderabad or Mumbai, India.

What is the work shift timing for this position?

The work shift timing for the Data Scientist position is from 2:00 PM to 11:00 PM IST.

What tools and technologies should the Data Scientist be familiar with?

The Data Scientist should be proficient in Python and common data science libraries, comfortable with cloud computing in Azure, and preferably have experience with Snowflake and ETL tools like Matillion and Azure Data Factory.

What type of company culture does Clarion Partners promote?

Clarion Partners promotes a culture that focuses on employee well-being and provides multidimensional support for a positive and healthy lifestyle, fostering a diverse and inclusive environment.

Does Clarion Partners offer any benefits?

Yes, Clarion Partners offers generous benefits including highly competitive health care coverage, a comprehensive 401K, company-sponsored volunteer opportunities, parental leave, childcare programs, and other benefits and discount purchase programs.

What is the reporting structure for this position?

The Data Scientist will be part of a global 24/7 team and will have a reporting line into the USA.

Is project management experience relevant for this role?

Yes, comfort with data science project/product management is preferred and is relevant for this role.

Global asset manager focused on delivering better client outcomes for over 75 years. Hello progress.

Finance
Industry
5001-10,000
Employees
1947
Founded Year

Mission & Purpose

Franklin Resources, operating under the brand name Franklin Templeton, is a global investment management company headquartered in San Mateo, California. Their primary objective is to provide investment solutions and expertise to individual and institutional investors worldwide. With a legacy spanning over seven decades, their ultimate mission is to deliver exceptional investment results while maintaining the highest level of integrity and commitment to their clients. Franklin Templeton aims to empower investors to achieve their financial goals by offering a wide range of investment products, including mutual funds, exchange-traded funds (ETFs), and discretionary portfolios, while adhering to their core values of putting clients first, acting with accountability and transparency, and fostering a culture of collaboration and innovation. Their purpose is to help investors navigate the complexities of the financial markets and make informed investment decisions that align with their long-term objectives.