Data Scientist - Retention

9 Months ago • 4-6 Years

Job Summary

Job Description

The Data Scientist will be responsible for developing a deep understanding of user journeys and generating data-driven insights and recommendations to guide product and customer success teams in their decision-making. This involves analyzing key product datasets to understand customer and product behavior, identifying growth opportunities, and building data-backed business cases. The role requires performing statistical analysis, developing and deploying predictive models, coordinating with different teams for implementation, and conducting ad-hoc analysis to generate actionable insights for stakeholders. The candidate will also be responsible for developing processes and tools to monitor model performance and data accuracy.
Must have:
  • 4-6 years of experience with real-world data and statistical models.
  • Proficient in Python (Pandas, Numpy, SciPy, Scikit-Learn, Seaborn, Plotly).
  • Hands-on knowledge of SQL and Excel.
  • Deep understanding of ML algorithms and their advantages/drawbacks.
  • Strong foundation in statistics and probability theory.
  • Strong communication and presentation skills
Good to have:
  • Experience in Gaming, E-Commerce, or B2C domain.

Job Details

Responsibilities: • Develop an in-depth understanding of user journeys and generate data driven insights & recommendations to help product and customer success teams in meticulous decision-making. • Define and analyse key product data sets to understand customer and product behaviour. • Work with stakeholders throughout the organization to identify opportunities for leveraging data to identify areas of growth and build strong data backed business cases around the same. • Perform statistical analysis/modelling on data and uncover hidden data patterns and correlations. • Perform feature engineering and develop and deploy predictive models/algorithms. • Coordinate with different teams to implement and deploy AI/ML driven models. • Conduct ad-hoc analysis around product areas for growth hacking and produce consumable reports for multiple business stakeholders. • Develop processes and tools to monitor and analyse model performance and data accuracy.
Technical Skills: • At least 4-6 years of experience of working with real-world data and building statistical models. • Hands-on experience of programming with Python, including working knowledge of packages like Pandas, Numpy, SciPy, Scikit-Learn,Seaborn,Plotly etc. • Hands-on knowledge of SQL and Excel. • Deep understanding of key supervised and unsupervised ML algorithms – should be able to explain what is happening under the hood and their real-world advantages/drawbacks. • Strong foundation of statistics and probability theory. • Knowledge of advanced statistical techniques and concepts (properties of distributions, statistical tests, simulations, Markov chain etc.) and experience with applications.
Other Skills: • Preferred Domain Experience: Gaming, E-Commerce, or any B2C experience. • Ability to break a problem into smaller chunks and design solution accordingly. • Ability to dive deeper into data, ask right questions, analyse with statistical methods and generate insights. • Ability to write modular, clean and well-documented code along with crisp design documents. • Strong communication and presentation skills.

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About The Company

We are one of India's oldest online skill-gaming companies that develop and operate zeal-driven applications for online gaming enthusiasts. With more than 60 million+ users and multiple brand verticals like A23 Rummy, A23 Poker A23 Games and Cricket.com, Head Digital Works has come a long way in the past 17 years. What started from a small garage in 2006 with nothing but a dream - "To become India's leading online gaming portal" has now turned into one of the most profitable start-ups in India that have gone through cycles of angel, venture capital and private equity investments.

We're a diverse group of thinkers and doers who are reimagining what's possible to make it easier for all of us to do what we love in new ways.

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