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3-7 Years
5 months ago
316 Viewed
530 Applied

Job Description

Take end-to-end ownership of a high impact data science project from
formulation, planning, architecting different solution approaches,
implementation at scale, measure and deliver.
Implement data-driven solutions based on advanced ML and optimization
algorithms to address business problems
Explore data using a variety of advanced statistical techniques to
proactively identify relationships, generate insights and answer business
questions or
Design and apply machine learning techniques to deliver actionable
insights from large-scale, multi structured datasets
Perform thorough model evaluation and devise ML / Deep Learning
experiments based on statistical analyses.
Act as an SME on the floor and help build data science capabilities

Requirements
Atleast 5 years of real-world experience working as a Data Scientist with
excellent skills in SQL and Python; additional knowledge of other data
mining software (Spark, etc.) is a plus
Comfortable working on both supervised and unsupervised machine
learning problems.
Worked on (at-least one of) the specialized packages pertaining to textual
data like NLTK and image data like pil, opencv etc.
Exposure to advanced deep learning techniques such as LSTM, CNN,
Dense neural networks as well as neural networks design and
implementation through tools like Tensorflow, Keras, PyTorch, DeepAI or
equivalent
Good understanding of data structures, algorithms, and first principles of
mathematics.
Basic understanding of statistics, linear algebra and calculus.
Experience with big data analytics and advanced data mining techniques
to analyse data
Experience of developing and deploying ML based solution into production
Experience with data visualization tools such as PowerBI, Tableau, Dash,
Plotly, D3.js, etc.
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About Kelp

Kelp (https://www.kelpglobal.com/) is an expert enterprise partner that provides end-to-end support for alternative investment firms, enabling professionals to make faster, better decisions, learn continuously and free-up bandwidth to focus on key drivers. Kelp provides 3 core products:

1. Deal Identification ingests data from multiple sources globally (paid, public, private, structured/unstructured and custom) and generates proprietary insights about sectors and companies of interest, enabling investors to create bespoke rolling shortlists and analyse acquisition targets.

2. Deal Management enables effective pipeline management and quality underwriting. By bringing together valuation trends, historical value bridges, investment decisions and market deals, Kelp powers consistent high-quality decisioning for the investment committee by eliminating biases and leveraging institutional learning.

3. Value Creation ingests and evaluates portfolio holding data against underwriting assumptions and exit projections. Auto-updated value bridges and exit scenarios enable effective monitoring of portfolio companies' performance against underwriting targets and prioritization of strategic / operational initiatives.

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