Data Scientist
Job Title: Data Scientist – Data and Artificial Intelligence
Location: Hyderabad
Job Type: Full-time
Company Description:
Qylis is a leading provider of innovative IT solutions, specializing in Cloud, Data & AI,
and Cyber Security. We help businesses unlock the full potential of these technologies
to achieve their goals and gain a competitive edge. Our unique approach focuses on
delivering value through bespoke solutions tailored to customer specific needs. We are
driven by a customer-centric mindset and committed to delivering continuous value
through intellectual property accelerators and automation. Our team of experts is
passionate about technology and dedicated to making a positive impact. We foster an
environment of growth and innovation, constantly pushing the boundaries to deliver
exceptional results. Website: www.qylis.com, LinkedIn:
www.linkedin.com/company/qylis
Job Summary
We are an engineering organization collaborating directly with clients to address
challenges using the latest technologies. Our focus is on joint code development with
clients' engineers for cloud-based solutions, accelerating organizational progress.
Working with product teams, partners, and open-source communities, we contribute to
open source, striving for platform improvement. This role involves creating impactful
solution patterns and open-source assets. As a team member, you'll collaborate with
engineers from both teams, applying your skills and creativity to solve complex
challenges and contribute to open source, while fostering professional growth.
Responsibilities
• Researching and developing production-grade models (forecasting, anomaly
detection, optimization, clustering, etc.) for global cloud business by using
statistical and machine learning techniques.
• Manage large volumes of data, and create new and improved solutions for data
collection, management, analyses, and data science model development.
• Drive the onboarding of new data and the refinement of existing data sources
through feature engineering and feature selection.
• Apply statistical concepts and cutting-edge machine learning techniques to
analyze cloud demand and optimize data science model code for distributed
computing platforms and task automation.
• Work closely with other data scientists and data engineers to deploy models that
drive cloud infrastructure capacity planning.
• Present analytical findings and business insights to project managers,
stakeholders, and senior leadership and keep abreast of new statistical /
machine learning techniques and implement them as appropriate to improve
predictive performance.
• Oversees the analysis of data and leads the team in identifying trends, patterns,
correlations, and insights to develop new forecasting models and improve
existing models.
• Leads collaboration among team and leverages data to identify pockets of
opportunity to apply state-of-the-art algorithms to improve a solution to a
business problem.
• Consistently leverages knowledge of techniques to optimize analysis using
algorithms.
• Modifies statistical analysis tools for evaluating Machine Learning models.
Solves deep and challenging problems for circumstances such as when model
predictions are not correct, when models do not match the training data or the
design outcomes when the data is not clean when it is unclear which analyses to
run, and when the process is ambiguous.
• Provides coaching to team members on business context, interpretation, and the
implications of findings. Interprets findings and their implications for multiple
businesses, and champions methodological rigour by calling attention to the
limitations of knowledge wherever biases in data, methods, and analysis exist.
• Generates and leverages insights that inform future studies and reframe the
research agenda. Informs both current business decisions by implementing and
adapting supply-chain strategies through complex business intelligence.
Qualifications
• M.Sc. in Statistics, Applied Mathematics, Applied Economics, Computer
Science or Engineering, Data Science, Operations Research or similar applied
quantitative field
• 7+ years of industry experience in developing production-grade statistical and
machine learning code in a collaborative team environment.
• Prior experience in machine learning using R or Python (scikit / numpy / pandas /
statsmodel).
• Prior experience working on Computer Vision Project is an Add on
• Knowledge on AWS and Azure Cloud.
• Prior experience in time series forecasting.
• Prior experience with typical data management systems and tools such as SQL.
• Knowledge and ability to work within a large-scale computing or big data context,
and hands-on experience with Hadoop, Spark, DataBricks or similar.
• Excellent analytical skills; ability to understand business needs and translate
them into technical solutions, including analysis specifications and models.
• Experience in machine learning using R or Python (scikit / numpy / pandas /
statsmodel) with skill level at or near fluency.
• Experience with deep learning models (e.g., tensorflow, PyTorch, CNTK) and solid
knowledge of theory and practice.
• Practical and professional experience contributing to and maintaining a large
code base with code versioning systems such as Git.
• Creative thinking skills with emphasis on developing innovative methods to solve
hard problems under ambiguity.
• Good interpersonal and communication (verbal and written) skills, including the
ability to write concise and accurate technical documentation and communicate
technical ideas to non-technical audiences.
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