Machine Learning (ML)
Data Science
PythonJob Summary
As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base
- Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
- Work with teams of smart collaborators. Be responsible for their appraisals and career development.
- Participate and lead executive presentations with client leadership stakeholders.
- Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
- See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.
Role & Responsibilities
- Serve as expert in Data Science, build framework to develop Production level DS/AI models.
- Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
- Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
- Lead and manage the onsite-offshore relation, at the same time adding value to the client.
- Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
- Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
- Present results, insights, and recommendations to senior management with an emphasis on the business impact.
- Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
- Lead or contribute to org level initiatives to build the Tredence of tomorrow.
Qualification & Experience
- Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
- 6-10+ years of experience in data science, building hands-on ML models
- Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
- Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
- Knowledge of programming languages SQL, Python/ R, Spark.
- Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
- Experience with cloud computing services (AWS, GCP or Azure)
- Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
- Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
- Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
- Knowledge in GPU code optimization, Spark MLlib Optimization.
- Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
- Experience with ML CI/CD pipelines.
Subodh Popalwar
Software Engineer, Memorres
About Tredence
About
Tredence is an analytics services and solutions company serving some of the leading Fortune 500 clients & successful track record of delivering business impact
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Follow CutshortSubodh Popalwar
Software Engineer, Memorres