Machine Learning (ML)
Python
Amazon Web Services (AWS)
Git
Postman
Data SciencePurpose of Job:
Responsible to lead a team of analysts to build and deploy predictive models to infuse core
business functions with deep analytical insights. The Senior Data Scientist will also work
closely with the Kinara management team to investigate strategically important business questions.
Job Responsibilities:
Lead a team through the entire analytical and machine learning model life cycle:
Define the problem statement
Build and clean datasets
Exploratory data analysis
Feature engineering
Apply ML algorithms and assess the performance
Code for deployment
Code testing and troubleshooting
Communicate Analysis to Stakeholders
Manage Data Analysts and Data Scientists
Qualifications:
Education: MS/MTech/Btech graduates or equivalent with a focus on data science and
quantitative fields (CS, Engineering, Mathematics, Economics)
Work Experience: 5+ years in a professional role with 3+ years in ML/AI
Other Requirements: ⮚ Domain knowledge in Financial Services is a big plus
Skills & Competencies
Technical Skills
⮚ Aptitude in Math and Stats
⮚ Proven experience in the use of Python, SQL, DevOps
⮚ Excellent in programming (Python), stats tools, and SQL
⮚ Working knowledge of tools and utilities - AWS, Git, Selenium, Postman,Prefect, Airflow, PySpark
Soft Skills
⮚ Deep Curiosity and Humility
⮚ Strong communications verbal and written
Subodh Popalwar
Software Engineer, Memorres
About Fintech Company
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Machine Learning (ML)Data SciencePythonWho we are looking for
· A Natural Language Processing (NLP) expert with strong computer science fundamentals and experience in working with deep learning frameworks. You will be working at the cutting edge of NLP and Machine Learning.
Roles and Responsibilities
· Work as part of a distributed team to research, build and deploy Machine Learning models for NLP.
· Mentor and coach other team members
· Evaluate the performance of NLP models and ideate on how they can be improved
· Support internal and external NLP-facing APIs
· Keep up to date on current research around NLP, Machine Learning and Deep Learning
Mandatory Requirements
· Any graduation with at least 2 years of demonstrated experience as a Data Scientist.
Behavioural Skills
· Strong analytical and problem-solving capabilities.
· Proven ability to multi-task and deliver results within tight time frames
· Must have strong verbal and written communication skills
· Strong listening skills and eagerness to learn
· Strong attention to detail and the ability to work efficiently in a team as well as individually
Technical Skills
Hands-on experience with
· NLP
· Deep Learning
· Machine Learning
· Python
· Bert
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· Experience in Computer Vision is preferred
Role: Data Scientist
Industry Type: Banking
Department: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning
Data ScienceMachine Learning (ML)
Deep Learning A Bachelor’s degree in data science, statistics, computer science, or a similar field
2+ years industry experience working in a data science role, such as statistics, machine learning,
deep learning, quantitative financial analysis, data engineering or natural language processing
Domain experience in Financial Services (banking, insurance, risk, funds) is preferred
Have and experience and be involved in producing and rapidly delivering minimum viable products,
results focused with ability to prioritize the most impactful deliverables
Strong Applied Statistics capabilities. Including excellent understanding of Machine Learning
techniques and algorithms
Hands on experience preferable in implementing scalable Machine Learning solutions using Python /
Scala / Java on Azure, AWS or Google cloud platform
Experience with storage frameworks like Hadoop, Spark, Kafka etc
Experience in building &deploying unsupervised, semi-supervised, and supervised models and be
knowledgeable in various ML algorithms such as regression models, Tree-based algorithms,
ensemble learning techniques, distance-based ML algorithms etc
Ability to track down complex data quality and data integration issues, evaluate different algorithmic
approaches, and analyse data to solve problems.
Experience in implementing parallel processing and in-memory frameworks such as H2O.ai
Data ScienceMachine Learning (ML)Pythono You’re both relentless and kind, and don’t see these as being mutually
exclusive
o You have a self-directed learning style, an insatiable curiosity, and a
hands-on execution mindset
o You have deep experience working with product and engineering teams
to launch machine learning products that users love in new or rapidly
evolving markets
o You flourish in uncertain environments and can turn incomplete,
conflicting, or ambiguous inputs into solid data-science action plans
o You bring best practices to feature engineering, model development, and
ML operations
o Your experience in deploying and monitoring the performance of models
in production enables us to implement a best-in-class solution
o You have exceptional writing and speaking skills with a talent for
articulating how data science can be applied to solve customer problems
Must-Have Qualifications
o Graduate degree in engineering, data science, mathematics, physics, or
another quantitative field
o 5+ years of hands-on experience in building and deploying production-
grade ML models with ML frameworks (TensorFlow, Keras, PyTorch) and
libraries like scikit-learn
o Track-record in building ML pipelines for time series, classification, and
predictive applications
o Expert level skills in Python for data analysis and visualization, hypothesis
testing, and model building
o Deep experience with ensemble ML approaches including random forests
and xgboost, and experience with databases and querying models for
structured and unstructured data
o A knack for using data visualization and analysis tools to tell a story
o You naturally think quantitatively about problems and work backward
from a customer outcome
What’ll make you stand out (but not required)
o You have a keen awareness or interest in network analysis/graph analysis
or NLP
o You have experience in distributed systems and graph databases
o You have a strong connection to finance teams or closely related
domains, the challenges they face, and a deep appreciation for their
aspirations
Responsibilities
> Selecting features, building and optimizing classifiers using machine
> learning techniques
> Data mining using state-of-the-art methods
> Extending company’s data with third party sources of information when
> needed
> Enhancing data collection procedures to include information that is
> relevant for building analytic systems
> Processing, cleansing, and verifying the integrity of data used for
> analysis
> Doing ad-hoc analysis and presenting results in a clear manner
> Creating automated anomaly detection systems and constant tracking of
> its performance
Key Skills
> Hands-on experience of analysis tools like R, Advance Python
> Must Have Knowledge of statistical techniques and machine learning
> algorithms
> Artificial Intelligence
> Understanding of Text analysis- Natural Language processing (NLP)
> Knowledge on Google Cloud Platform
> Advanced Excel, PowerPoint skills
> Advanced communication (written and oral) and strong interpersonal
> skills
> Ability to work cross-culturally
> Good to have Deep Learning
> VBA and visualization tools like Tableau, PowerBI, Qliksense, Qlikview
> will be an added advantage
Machine Learning (ML)Data Science1.Advanced knowledge of statistical techniques, NLP, machine learning algorithms and deep
learning
frameworks like Tensorflow, Theano, Keras, Pytorch
2. Proficiency with modern statistical modeling (regression, boosting trees, random forests,
etc.),
machine learning (text mining, neural network, NLP, etc.), optimization (linear
optimization,
nonlinear optimization, stochastic optimization, etc.) methodologies.
3. Build complex predictive models using ML and DL techniques with production quality
code and jointly
own complex data science workflows with the Data Engineering team.
4. Familiar with modern data analytics architecture and data engineering technologies
(SQL and No-SQL databases)
5. Knowledge of REST APIs and Web Services
6. Experience with Python, R, sh/bash
Required Skills (Non-Technical):-
1. Fluent in English Communication (Spoken and verbal)
2. Should be a team player
3. Should have a learning aptitude
4. Detail-oriented, analytical and inquisitive
5. Ability to work independently and with others
6. Extremely organized with strong time-management skills
7. Problem Solving & Critical Thinking
Required Experience Level :- Senior level- 4+Years
Work Location : Pune preferred, Remote option available
Work Timing : 2:30 PM to 11:30 PM IST
Data ScienceMachine Learning (ML)
R ProgrammingPython
Data ScienceMachine Learning (ML)Deep LearningLocation: Pune
Experience: 3+ Years
Experience applying statistical methods (distribution analysis, classification, clustering, etc.).
The individual requires excellent analytical skills required to mine data, develop algorithms and then analyze results to determine decisions or actions
At least good experience in using data science with a focus on deep neural nets, statistics, empirical data analysis, machine learning and Natural Language Processing
Solid knowledge of various statistical techniques and experience using machine learning algorithms
Ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets
Excellent relationship management skills with senior stakeholders is paramount
Experience in practical data processing, data mining, text mining and information retrieval tasks
Machine Learning (ML)Responsibilities:
- Develop REST/JSON API’s Design code for high scale/availability/resiliency.
- Develop responsive web apps and integrate APIs using NodeJS.
- Presenting Chat efficiency reports to higher Management
- Develop system flow diagrams to automate a business function and identify impacted systems; metrics to depict the cost benefit analysis of the solutions developed.
- Work closely with business operations to convert requirements into system solutions and collaborate with development teams to ensure delivery of highly scalable and available systems.
- Using tools to classify/categorize the chat based on intents and coming up with F1 score for Chat Analysis
- Experience in analyzing real agents Chat conversation with agent to train the Chatbot.
- Developing Conversational Flows in the chatbot
- Calculating Chat efficiency reports.
Good to Have:
- Monitors performance and quality control plans to identify performance.
- Works on problems of moderate and varied complexity where analysis of data may require adaptation of standardized practices.
- Works with management to prioritize business and information needs.
- Experience in analyzing real agents Chat conversation with agent to train the Chatbot.
- Identifies, analyzes, and interprets trends or patterns in complex data sets.
- Ability to manage multiple assignments.
- Understanding of ChatBot Architecture.
- Experience of Chatbot training
Data ScienceMachine Learning (ML)PythonResponsibilities for Data Scientist/ NLP Engineer
Work with customers to identify opportunities for leveraging their data to drive business
solutions.
• Develop custom data models and algorithms to apply to data sets.
• Basic data cleaning and annotation for any incoming raw data.
• Use predictive modeling to increase and optimize customer experiences, revenue
generation, ad targeting and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Deployment of ML model in production.
Qualifications for Junior Data Scientist/ NLP Engineer
• BS, MS in Computer Science, Engineering, or related discipline.
• 3+ Years of experience in Data Science/Machine Learning.
• Experience with programming language Python.
• Familiar with at least one database query language, such as SQL
• Knowledge of Text Classification & Clustering, Question Answering & Query Understanding,
Search Indexing & Fuzzy Matching.
• Excellent written and verbal communication skills for coordinating acrossteams.
• Willing to learn and master new technologies and techniques.
• Knowledge and experience in statistical and data mining techniques:
GLM/Regression, Random Forest, Boosting, Trees, text mining, NLP, etc.
• Experience with chatbots would be bonus but not required
PythonDeep LearningMachine Learning (ML)
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Software Engineer, Memorres