This will include:
Scorecards
Strategies
MIS
The verticals included are:
Risk
Marketing
Product
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About us
SteelEye is the only regulatory compliance technology and data analytics firm that offers transaction reporting, record keeping, trade reconstruction, best execution and data insight in one comprehensive solution. The firm’s scalable secure data storage platform offers encryption at rest and in flight and best-in-class analytics to help financial firms meet regulatory obligations and gain competitive advantage.
The company has a highly experienced management team and a strong board, who have decades of technology and management experience and worked in senior positions at many leading international financial businesses. We are a young company that shares a commitment to learning, being smart, working hard and being honest in all we do and striving to do that better each day. We value all our colleagues equally and everyone should feel able to speak up, propose an idea, point out a mistake and feel safe, happy and be themselves at work.
Being part of a start-up can be equally exciting as it is challenging. You will be part of the SteelEye team not just because of your talent but also because of your entrepreneurial flare which we thrive on at SteelEye. This means we want you to be curious, contribute, ask questions and share ideas. We encourage you to get involved in helping shape our business. What you'll do
What you will do?
- Deliver plugins for our python based ETL pipelines.
- Deliver python services for provisioning and managing cloud infrastructure.
- Design, Develop, Unit Test, and Support code in production.
- Deal with challenges associated with large volumes of data.
- Manage expectations with internal stakeholders and context switch between multiple deliverables as priorities change.
- Thrive in an environment that uses AWS and Elasticsearch extensively.
- Keep abreast of technology and contribute to the evolution of the product.
- Champion best practices and provide mentorship.
What we're looking for
- Python 3.
- Python libraries used for data (such as pandas, numpy).
- AWS.
- Elasticsearch.
- Performance tuning.
- Object Oriented Design and Modelling.
- Delivering complex software, ideally in a FinTech setting.
- CI/CD tools.
- Knowledge of design patterns.
- Sharp analytical and problem-solving skills.
- Strong sense of ownership.
- Demonstrable desire to learn and grow.
- Excellent written and oral communication skills.
- Mature collaboration and mentoring abilities.
What will you get?
- This is an individual contributor role. So, if you are someone who loves to code and solve complex problems and build amazing products and not worry about anything else, this is the role for you.
- You will have the chance to learn from the best in the business who have worked across the world and are technology geeks.
- Company that always appreciates ownership and initiative. If you are someone who is full of ideas, this role is for you.
Title: Data Engineer (Azure) (Location: Gurgaon/Hyderabad)
Salary: Competitive as per Industry Standard
We are expanding our Data Engineering Team and hiring passionate professionals with extensive
knowledge and experience in building and managing large enterprise data and analytics platforms. We
are looking for creative individuals with strong programming skills, who can understand complex
business and architectural problems and develop solutions. The individual will work closely with the rest
of our data engineering and data science team in implementing and managing Scalable Smart Data
Lakes, Data Ingestion Platforms, Machine Learning and NLP based Analytics Platforms, Hyper-Scale
Processing Clusters, Data Mining and Search Engines.
What You’ll Need:
- 3+ years of industry experience in creating and managing end-to-end Data Solutions, Optimal
Data Processing Pipelines and Architecture dealing with large volume, big data sets of varied
data types.
- Proficiency in Python, Linux and shell scripting.
- Strong knowledge of working with PySpark dataframes, Pandas dataframes for writing efficient pre-processing and other data manipulation tasks.
● Strong experience in developing the infrastructure required for data ingestion, optimal
extraction, transformation, and loading of data from a wide variety of data sources using tools like Azure Data Factory, Azure Databricks (or Jupyter notebooks/ Google Colab) (or other similiar tools).
- Working knowledge of github or other version control tools.
- Experience with creating Restful web services and API platforms.
- Work with data science and infrastructure team members to implement practical machine
learning solutions and pipelines in production.
- Experience with cloud providers like Azure/AWS/GCP.
- Experience with SQL and NoSQL databases. MySQL/ Azure Cosmosdb / Hbase/MongoDB/ Elasticsearch etc.
- Experience with stream-processing systems: Spark-Streaming, Kafka etc and working experience with event driven architectures.
- Strong analytic skills related to working with unstructured datasets.
Good to have (to filter or prioritize candidates)
- Experience with testing libraries such as pytest for writing unit-tests for the developed code.
- Knowledge of Machine Learning algorithms and libraries would be good to have,
implementation experience would be an added advantage.
- Knowledge and experience of Datalake, Dockers and Kubernetes would be good to have.
- Knowledge of Azure functions , Elastic search etc will be good to have.
- Having experience with model versioning (mlflow) and data versioning will be beneficial
- Having experience with microservices libraries or with python libraries such as flask for hosting ml services and models would be great.
- Proficiency in shell scripting
- Proficiency in automation of tasks
- Proficiency in Pyspark/Python
- Proficiency in writing and understanding of sqoop
- Understanding of CloudEra manager
- Good understanding of RDBMS
- Good understanding of Excel
- Hands-on programming expertise in Java OR Python
- Strong production experience with Spark (Minimum of 1-2 years)
- Experience in data pipelines using Big Data technologies (Hadoop, Spark, Kafka, etc.,) on large scale unstructured data sets
- Working experience and good understanding of public cloud environments (AWS OR Azure OR Google Cloud)
- Experience with IAM policy and role management is a plus
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)
- Must have 5-8 years of experience in handling data
- Must have the ability to interpret large amounts of data and to multi-task
- Must have strong knowledge of and experience with programming (Python), Linux/Bash scripting, databases(SQL, etc)
- Must have strong analytical and critical thinking to resolve business problems using data and tech
- Must have domain familiarity and interest of – Cloud technologies (GCP/Azure Microsoft/ AWS Amazon), open-source technologies, Enterprise technologies
- Must have the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Must have good communication skills
- Working knowledge/exposure to ElasticSearch, PostgreSQL, Athena, PrestoDB, Jupyter Notebook
Responsibilities:
- Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
- Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
- Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
- Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
- Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
- Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
- Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
- Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
- Drive analytics thought leadership and effectively contributes towards transformational initiatives.
- Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.