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Role : Sr Data Scientist / Tech Lead – Data Science

Number of positions : 8

Responsibilities

• Lead a team of data scientists, machine learning engineers and big data specialists
• Be the main point of contact for the customers
• Lead data mining and collection procedures
• Ensure data quality and integrity
• Interpret and analyze data problems
• Conceive, plan and prioritize data projects
• Build analytic systems and predictive models
• Test performance of data-driven products
• Visualize data and create reports
• Experiment with new models and techniques
• Align data projects with organizational goals

Requirements (please read carefully)

• Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
• Msc-Statistics/ Phd.Statistics
• Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
• Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
• Proven experience as a Data Scientist or similar role, for about 7-8 years
• Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
• Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
• Knowledge of data management and visualization techniques --- more from a Data Science perspective.
• Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
• Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.

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• Minimum 1 years of relevant experience, in PySpark (mandatory)
• Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus 
• Ability to play lead role and independently manage 3-5 member of Pyspark development team 
• EMR ,Python and PYspark mandate.
• Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS

Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

What will you do?

• You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
• You will be constantly assessing and improving the model using techniques like Transfer learning
• You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
• You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Building predictive models and machine-learning algorithms to apply to data sets.
• Coordinate with different functional teams to implement models and monitor outcomes.
•  
• Presenting information using data visualization techniques and proposing solutions and strategies to business challenges

We would love to hear from you if :

• You have 2+ years of experience as a software engineer at a SaaS or technology company
• Demonstrable hands-on programming experience with Python/R Data Science Stack
• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
• Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Preferable Experience Experienced in web crawling and data scraping
• Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
• Experience with text mining, pattern matching and fuzzy matching

• Brand new Macbook
• Stock Options
• Health Insurance
• Unlimited Sick Leaves
• Passion Fund (Invest in yourself or your passion project)
• Wind Down

• Adept at Machine learning techniques and algorithms.

Feature selection, dimensionality reduction, building and

• optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Doing ad-hoc analysis and presenting results
• Proficiency in using query languages such as N1QL, SQL

Experience with data visualization tools, such as D3.js, GGplot,

• Plotly, PyPlot, etc.

Creating automated anomaly detection systems and constant tracking

• of its performance
• Strong in Python is a must.
• Strong in Data Analysis and mining is a must
• Deep Learning, Neural Network, CNN, Image Processing (Must)

Building analytic systems - data collection, cleansing and

• integration

Experience with NoSQL databases, such as Couchbase, MongoDB,

Cassandra, HBase

CommerceIQ is Hiring Data Scientist (3-5 yrs)

At CommerceIQ, we are building the world’s most sophisticated E-commerce Channel Optimization software to help brands leverage Machine Learning, Analytics and Automation to grow their E-commerce business on all channels, globally.

Using CommerceIQ as a single source of truth, customers have driven 40% increase in incremental sales, 20% improvement in profitability and 32% reduction in out of stock rates on Amazon.

What You’ll Be Doing

As a Senior Data Scientist, you will work closely with Engineering/Product/Operations teams to build state-of-the-art ML based solutions for B2B SaaS products. This entails not only leveraging advanced techniques for predictions, time-series forecasting, topic modelling, optimisation but deep understanding of business and product too.

• Apply excellent problem solving skills to deconstruct and formulate solutions from first-principles

• Work on data science roadmap and build the core engine of our flagship CommerceIQ product

• Collaborate with product and engineering to design product strategy, identify key metrics to drive and support with proof of concept

• Perform rapid prototyping of experimental solutions and develop robust, sustainable and scalable production systems

• Work with large scale ecommerce data of the biggest brands on amazon

• Apply out-of-the-box, advanced algorithms to complex problems in real-time systems

• Drive productization of techniques to be made available to a wide range of customers

• You would be working with and mentoring fellow team members on the owned charter

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 4+ years of experience in solving data science problems that have driven value to customers

• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra. Experience in NLP would be an advantage

• Hands-on programming skills and ability to write modular and scalable code in Python/R. Knowledge of SQL is required

• Familiarity with distributed computing architecture like Spark, Map-Reduce paradigm and Hadoop will be an added advantage

• Strong spoken and written communication skills, able to explain complex ideas in a simple, intuitive manner, write/maintain good technical documentation on projects

• Experience with building ML data products in an engineering organization interfacing with other teams and departments to deliver impact

• We are looking for candidates who are curious and self-starters; obsess over customer problems to deliver maximum value to them.
• Data scientist, Machine Learning, data science, data analyst

Job Type: Full-time

Experience:

• Data Scientist: 3 years (Required)

Application Question:

• Looking for product based industry experience from tier 1 /tier 2 colleges (NIT ,BIT, IIT,IIIT, BITS, Strong Profiles)